A temporal mechanism for generating the phase precession of hippocampal place cells

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.

Septo-hippocampal dynamics and the encoding of space and time

Encoding an event in memory requires neural activity to represent multiple dimensions of behavioral experience in space and time. Recent experiments have explored the influence of neural dynamics regulated by the medial septum on the functional encoding of space and time by neurons in the hippocampus and associated structures. This review addresses these dynamics, focusing on the role of theta rhythm, the differential effects of septal inactivation and activation on the functional coding of space and time by individual neurons, and the influence on phase coding that appears as phase precession. We also discuss data indicating that theta rhythm plays a role in timing the internal dynamics of memory encoding and retrieval, as well as the behavioral influences of these neuronal manipulations with regard to memory function.

Spectrum Degradation of Hippocampal LFP During Euthanasia

The hippocampal local field potential (LFP) exhibits a strong correlation with behavior. During rest, the theta rhythm is not prominent, but during active behavior, there are strong rhythms in the theta, theta harmonics, and gamma ranges. With increasing running velocity, theta, theta harmonics and gamma increase in power and in cross-frequency coupling, suggesting that neural entrainment is a direct consequence of the total excitatory input. While it is common to study the parametric range between the LFP and its complementing power spectra between deep rest and epochs of high running velocity, it is also possible to explore how the spectra degrades as the energy is completely quenched from the system. Specifically, it is unknown whether the 1/f slope is preserved as synaptic activity becomes diminished, as low frequencies are generated by large pools of neurons while higher frequencies comprise the activity of more local neuronal populations. To test this hypothesis, we examined rat LFPs recorded from the hippocampus and entorhinal cortex during barbiturate overdose euthanasia. Within the hippocampus, the initial stage entailed a quasi-stationary LFP state with a power-law feature in the power spectral density. In the second stage, there was a successive erosion of power from high- to low-frequencies in the second stage that continued until the only dominant remaining power was <20 Hz. This stage was followed by a rapid collapse of power spectrum toward the absolute electrothermal noise background. As the collapse of activity occurred later in hippocampus compared with medial entorhinal cortex, it suggests that the ability of a neural network to maintain the 1/f slope with decreasing energy is a function of general connectivity. Broadly, these data support the energy cascade theory where there is a cascade of energy from large cortical populations into smaller loops, such as those that supports the higher frequency gamma rhythm. As energy is pulled from the system, neural entrainment at gamma frequency (and higher) decline first. The larger loops, comprising a larger population, are fault-tolerant to a point capable of maintaining their activity before a final collapse.

Neural mechanisms of navigation involving interactions of cortical and subcortical structures

Animals must perform spatial navigation for a range of different behaviors, including selection of trajectories toward goal locations and foraging for food sources. To serve this function, a number of different brain regions play a role in coding different dimensions of sensory input important for spatial behavior, including the entorhinal cortex, the retrosplenial cortex, the hippocampus, and the medial septum. This article will review data concerning the coding of the spatial aspects of animal behavior, including location of the animal within an environment, the speed of movement, the trajectory of movement, the direction of the head in the environment, and the position of barriers and objects both relative to the animal's head direction (egocentric) and relative to the layout of the environment (allocentric). The mechanisms for coding these important spatial representations are not yet fully understood but could involve mechanisms including integration of self-motion information or coding of location based on the angle of sensory features in the environment. We will review available data and theories about the mechanisms for coding of spatial representations. The computation of different aspects of spatial representation from available sensory input requires complex cortical processing mechanisms for transformation from egocentric to allocentric coordinates that will only be understood through a combination of neurophysiological studies and computational modeling.

Asymmetry of the temporal code for space by hippocampal place cells

Hippocampal place cells convey spatial information through spike frequency (“rate coding”) and spike timing relative to the theta phase (“temporal coding”). Whether rate and temporal coding are due to independent or related mechanisms has been the subject of wide debate. Here we show that the spike timing of place cells couples to theta phase before major increases in firing rate, anticipating the animal’s entrance into the classical, rate-based place field. In contrast, spikes rapidly decouple from theta as the animal leaves the place field and firing rate decreases. Therefore, temporal coding has strong asymmetry around the place field center. We further show that the dynamics of temporal coding along space evolves in three stages as the animal traverses the place field: phase coupling, sharp precession and phase decoupling. These results suggest that independent mechanisms may govern rate and temporal coding.

Neural Mechanism to Simulate a Scale-Invariant Future

Predicting the timing and order of future events is an essential feature of cognition in higher life forms. We propose a neural mechanism to nondestructively translate the current state of spatiotemporal memory into the future, so as to construct an ordered set of future predictions almost instantaneously. We hypothesize that within each cycle of hippocampal theta oscillations, the memory state is swept through a range of translations to yield an ordered set of future predictions through modulations in synaptic connections. Theoretically, we operationalize critical neurobiological findings from hippocampal physiology in terms of neural network equations representing spatiotemporal memory. Combined with constraints based on physical principles requiring scale invariance and coherence in translation across memory nodes, the proposition results in Weber-Fechner spacing for the representation of both past (memory) and future (prediction) timelines. We show that the phenomenon of phase precession of neurons in the hippocampus and ventral striatum correspond to the cognitive act of future prediction.

State-dependencies of learning across brain scales

Learning is a complex brain function operating on different time scales, from milliseconds to years, which induces enduring changes in brain dynamics. The brain also undergoes continuous “spontaneous” shifts in states, which, amongst others, are characterized by rhythmic activity of various frequencies. Besides the most obvious distinct modes of waking and sleep, wake-associated brain states comprise modulations of vigilance and attention. Recent findings show that certain brain states, particularly during sleep, are essential for learning and memory consolidation. Oscillatory activity plays a crucial role on several spatial scales, for example in plasticity at a synaptic level or in communication across brain areas. However, the underlying mechanisms and computational rules linking brain states and rhythms to learning, though relevant for our understanding of brain function and therapeutic approaches in brain disease, have not yet been elucidated. Here we review known mechanisms of how brain states mediate and modulate learning by their characteristic rhythmic signatures. To understand the critical interplay between brain states, brain rhythms, and learning processes, a wide range of experimental and theoretical work in animal models and human subjects from the single synapse to the large-scale cortical level needs to be integrated. By discussing results from experiments and theoretical approaches, we illuminate new avenues for utilizing neuronal learning mechanisms in developing tools and therapies, e.g., for stroke patients and to devise memory enhancement strategies for the elderly.

Back to the future: preserved hippocampal network activity during reverse ambulation

During movement, there is a transition of activity across the population, such that place-field centers ahead of the rat are sequentially activated in the order that they will be encountered. Although the mechanisms responsible for this sequence updating are unknown, two classes of models can be considered. The first class involves head-direction information for activating neurons in the order that their place fields will be traversed. An alternative model contends that motion and turn-related information from the posterior parietal cortex shift the subset of active hippocampal cells across the population. To explicitly test these two models, rodents were trained to run backward on a linear track, placing movement in opposition with head orientation. Although head-direction did not change between running conditions, place-field activity remapped and there was an increase in place-field size during backward running compared with forward. The population activity, however, could still be used to reconstruct the location of the rat accurately. Moreover, theta phase precession was maintained in both running conditions, indicating preservation of place-field sequences on short-time scales. The observation that sequence encoding persists even when the animal is orientated away from the direction of movement favors the concept that posterior parietal cortical mechanisms may be partially responsible for updating hippocampal activity patterns.

Modeling inheritance of phase precession in the hippocampal formation

Spatial information about the environment is encoded by the activity of place and grid cells in the hippocampal formation. As an animal traverses a cell's firing field, action potentials progressively shift to earlier phases of the theta oscillation (6-10 Hz). This "phase precession" is observed also in the prefrontal cortex and the ventral striatum, but mechanisms for its generation are unknown. However, once phase precession exists in one region, it might also propagate to downstream regions. Using a computational model, we analyze such inheritance of phase precession, for example, from the entorhinal cortex to CA1 and from CA3 to CA1. We find that distinctive subthreshold and suprathreshold features of the membrane potential of CA1 pyramidal cells (Harvey et al., 2009; Mizuseki et al., 2012; Royer et al., 2012) can be explained by inheritance and that excitatory input is essential. The model explains how inhibition modulates the slope and range of phase precession and provides two main testable predictions. First, theta-modulated inhibitory input to a CA1 pyramidal cell is not necessary for phase precession. Second, theta-modulated inhibitory input on its own generates membrane potential peaks that are in phase with peaks of the extracellular field. Furthermore, we suggest that the spatial distribution of field centers of a population of phase-precessing input cells determines, not only the place selectivity, but also the characteristics of phase precession of the targeted output cell. The inheritance model thus can explain why phase precession is observed throughout the hippocampal formation and other areas of the brain.

Hippocampal phase precession from dual input components

Phase precession is a well known phenomenon in which a hippocampal place cell will fire action potentials at successively earlier phases (relative to the theta-band oscillations recorded in the local field potential) as an animal moves through the cell's receptive field (also known as a place field). We present a model in which CA1 pyramidal cell spiking is driven by dual input components arising from CA3 and EC3. The receptive fields of these two input components overlap but are offset in space from each other such that as the animal moves through the model place field, action potentials are driven first by the CA3 input component and then the EC3 input component. As CA3 synaptic input is known to arrive in CA1 at a later theta phase than EC3 input (Mizuseki et al., 2009; Montgomery et al., 2009), CA1 spiking advances in phase as the model transitions from CA3-driven spiking to EC3-driven spiking. Here spike phase is a function of animal location, placing our results in agreement with many experimental observations characterizing CA1 phase precession (O'Keefe and Recce, 1993; Huxter et al., 2003; Geisler et al., 2007). We predict that experimental manipulations that dramatically enhance or disrupt activity in either of these areas should have a significant effect on phase precession observed in CA1.

Phase precession through acceleration of local theta rhythm: a biophysical model for the interaction between place cells and local inhibitory neurons

Phase precession is one of the most well known examples within the temporal coding hypothesis. Here we present a biophysical spiking model for phase precession in hippocampal CA1 which focuses on the interaction between place cells and local inhibitory interneurons. The model's functional block is composed of a place cell (PC) connected with a local inhibitory cell (IC) which is modulated by the population theta rhythm. Both cells receive excitatory inputs from the entorhinal cortex (EC). These inputs are both theta modulated and space modulated. The dynamics of the two neuron types are described by integrate-and-fire models with conductance synapses, and the EC inputs are described using non-homogeneous Poisson processes. Phase precession in our model is caused by increased drive to specific PC/IC pairs when the animal is in their place field. The excitation increases the IC's firing rate, and this modulates the PC's firing rate such that both cells precess relative to theta. Our model implies that phase coding in place cells may not be independent from rate coding. The absence of restrictive connectivity constraints in this model predicts the generation of phase precession in any network with similar architecture and subject to a clocking rhythm, independently of the involvement in spatial tasks.

Sensory feedback, error correction, and remapping in a multiple oscillator model of place-cell activity

Mammals navigate by integrating self-motion signals ("path integration") and occasionally fixing on familiar environmental landmarks. The rat hippocampus is a model system of spatial representation in which place cells are thought to integrate both sensory and spatial information from entorhinal cortex. The localized firing fields of hippocampal place cells and entorhinal grid-cells demonstrate a phase relationship with the local theta (6-10 Hz) rhythm that may be a temporal signature of path integration. However, encoding self-motion in the phase of theta oscillations requires high temporal precision and is susceptible to idiothetic noise, neuronal variability, and a changing environment. We present a model based on oscillatory interference theory, previously studied in the context of grid cells, in which transient temporal synchronization among a pool of path-integrating theta oscillators produces hippocampal-like place fields. We hypothesize that a spatiotemporally extended sensory interaction with external cues modulates feedback to the theta oscillators. We implement a form of this cue-driven feedback and show that it can retrieve fixed points in the phase code of position. A single cue can smoothly reset oscillator phases to correct for both systematic errors and continuous noise in path integration. Further, simulations in which local and global cues are rotated against each other reveal a phase-code mechanism in which conflicting cue arrangements can reproduce experimentally observed distributions of "partial remapping" responses. This abstract model demonstrates that phase-code feedback can provide stability to the temporal coding of position during navigation and may contribute to the context-dependence of hippocampal spatial representations. While the anatomical substrates of these processes have not been fully characterized, our findings suggest several signatures that can be evaluated in future experiments.

Network mechanisms of theta related neuronal activity in hippocampal CA1 pyramidal neurons

Although hippocampal theta oscillations represent a prime example of temporal coding in the mammalian brain, little is known about the specific biophysical mechanisms. Intracellular recordings support a particular abstract oscillatory interference model of hippocampal theta activity, the soma-dendrite interference model. To gain insight into the cellular and circuit level mechanisms of theta activity, we implemented a similar form of interference using the actual hippocampal network in mice in vitro. We found that pairing increasing levels of phasic dendritic excitation with phasic stimulation of perisomatic projecting inhibitory interneurons induced a somatic polarization and action potential timing profile that reproduced most common features. Alterations in the temporal profile of inhibition were required to fully capture all features. These data suggest that theta-related place cell activity is generated through an interaction between a phasic dendritic excitation and a phasic perisomatic shunting inhibition delivered by interneurons, a subset of which undergo activity-dependent presynaptic modulation.

Independence of the unimodal tuning of firing rate from theta phase precession in hippocampal place cells

There are two prominent features for place cells in rat hippocampus. The firing rate remarkably increases when rat enters the cell's place field and reaches a maximum around the center of place field, and it decreases when the animal approaches the end of the place field. Simultaneously the spikes gradually and monotonically advance to earlier phase relative to hippocampal theta rhythm as the rat traverses along the cell's place field, known as temporal coding. In this paper, we investigate whether two main characteristics of place cell firing are independent or not by mainly focusing on the generation mechanism of the unimodal tuning of firing rate by using a reduced CA1 two-compartment neuron model. Based on recent evidences, we hypothesize that the coupling of dendritic with the somatic compartment is not constant but dynamically regulated as the animal moves further along the place field, in contrast to previous two-compartment modeling. Simulations show that the regulable coupling is critically responsible for the generation of unimodal firing rate profile in place cells, independent of phase precession. Predictions of our model accord well with recent observations like occurrence of phase precession with very low as well as high firing rate (Huxter et al. Nature 425:828-832, 2003) and persistency of phase precession after transient silence of hippocampus activity (Zugaro et al. Nat Neurosci 8:67-71, 2005.

The 2008 Judith Hoyer lecture: epilepsy in children: listening to mothers

The incidence of epilepsy is significantly higher in children than adults. When faced with the diagnosis of epilepsy, parents have many questions regarding cause, treatment, and prognosis. Although the majority of children with epilepsy have an excellent prognosis and respond well to therapy, some children are refractory to therapy and suffer from cognitive decline. Animal models are now providing insights into the mechanisms responsible for the high incidence of seizures during development and age-dependent seizure-induced damage. One of the causes of the increased susceptibility of the young brain to seizures is the depolarizing effects of GABA secondary to high intracellular concentrations of chloride in young neurons. Although cell loss is not a feature of seizures in the young brain, recurrent seizures do result in aberrant sprouting of mossy fibers, reduce neurogenesis, and alter excitatory and inhibitory neurotransmitter receptor structure and function. Behavioral consequences of early-life seizures include impaired spatial cognition, which now can be assessed using single-cell recordings from the hippocampus. Antiepileptic drugs have had a tremendous positive influence in epilepsy management, although there are now a number of studies demonstrating that antiepileptic drugs at therapeutic concentrations can impair cognition and result in increased apoptosis. While clinical judgment and experience are paramount when discussing the consequences of seizures and their treatment, awareness of studies from animals can provide the clinician with guidance in addressing these important issues with parents.

Arc length coding by interference of theta frequency oscillations may underlie context-dependent hippocampal unit data and episodic memory function

Many memory models focus on encoding of sequences by excitatory recurrent synapses in region CA3 of the hippocampus. However, data and modeling suggest an alternate mechanism for encoding of sequences in which interference between theta frequency oscillations encodes the position within a sequence based on spatial arc length or time. Arc length can be coded by an oscillatory interference model that accounts for many features of the context-dependent firing properties of hippocampal neurons observed during performance of spatial memory tasks. In continuous spatial alternation, many neurons fire selectively depending on the direction of prior or future response (left or right). In contrast, in delayed non-match to position, most neurons fire selectively for task phase (sample vs. choice), with less selectivity for left versus right. These seemingly disparate results are effectively simulated by the same model, based on mechanisms similar to a model of grid cell firing in entorhinal cortex. The model also simulates forward shifting of firing over trials. Adding effects of persistent firing with reset at reward locations addresses changes in context-dependent firing with different task designs. Arc length coding could contribute to episodic encoding of trajectories as sequences of states and actions.

Network and intrinsic cellular mechanisms underlying theta phase precession of hippocampal neurons

Hippocampal 'place cells' systematically shift their phase of firing in relation to the theta rhythm as an animal traverses the 'place field'. These dynamics imply that the neural ensemble begins each theta cycle at a point in its state-space that might 'represent' the current location of the rat, but that the ensemble 'looks ahead' during the rest of the cycle. Phase precession could result from intrinsic cellular dynamics involving interference of two oscillators of different frequencies, or from network interactions, similar to Hebb's 'phase sequence' concept, involving asymmetric synaptic connections. Both models have difficulties accounting for all of the available experimental data, however. A hybrid model, in which the look-ahead phenomenon implied by phase precession originates in superficial entorhinal cortex by some form of interference mechanism and is enhanced in the hippocampus proper by asymmetric synaptic plasticity during sequence encoding, seems to be consistent with available data, but as yet there is no fully satisfactory theoretical account of this phenomenon. This review is part of the INMED/TINS special issue Physiogenic and pathogenic oscillations: the beauty and the beast, based on presentations at the annual INMED/TINS symposium (http://inmednet.com).

Hippocampal place cell assemblies are speed-controlled oscillators

The phase of spikes of hippocampal pyramidal cells relative to the local field theta oscillation shifts forward ("phase precession") over a full theta cycle as the animal crosses the cell's receptive field ("place field"). The linear relationship between the phase of the spikes and the travel distance within the place field is independent of the animal's running speed. This invariance of the phase-distance relationship is likely to be important for coordinated activity of hippocampal cells and space coding, yet the mechanism responsible for it is not known. Here we show that at faster running speeds place cells are active for fewer theta cycles but oscillate at a higher frequency and emit more spikes per cycle. As a result, the phase shift of spikes from cycle to cycle (i.e., temporal precession slope) is faster, yet spatial-phase precession stays unchanged. Interneurons can also show transient-phase precession and contribute to the formation of coherently precessing assemblies. We hypothesize that the speed-correlated acceleration of place cell assembly oscillation is responsible for the phase-distance invariance of hippocampal place cells.

Theta phase precession emerges from a hybrid computational model of a CA3 place cell

The origins and functional significance of theta phase precession in the hippocampus remain obscure, in part, because of the difficulty of reproducing hippocampal place cell firing in experimental settings where the biophysical underpinnings can be examined in detail. The present study concerns a neurobiologically based computational model of the emergence of theta phase precession in which the responses of a single model CA3 pyramidal cell are examined in the context of stimulation by realistic afferent spike trains including those of place cells in entorhinal cortex, dentate gyrus, and other CA3 pyramidal cells. Spike-timing dependent plasticity in the model CA3 pyramidal cell leads to a spatially correlated associational synaptic drive that subsequently creates a spatially asymmetric expansion of the model cell's place field. Following an initial training period, theta phase precession can be seen in the firing patterns of the model CA3 pyramidal cell. Through selective manipulations of the model it is possible to decompose theta phase precession in CA3 into the separate contributing factors of inheritance from upstream afferents in the dentate gyrus and entorhinal cortex, the interaction of synaptically controlled increasing afferent drive with phasic inhibition, and the theta phase difference between dentate gyrus granule cell and CA3 pyramidal cell activity. In the context of a single CA3 pyramidal cell, the model shows that each of these factors plays a role in theta phase precession within CA3 and suggests that no one single factor offers a complete explanation of the phenomenon. The model also shows parallels between theta phase encoding and pattern completion within the CA3 autoassociative network.

Phase precession in hippocampal interneurons showing strong functional coupling to individual pyramidal cells

Although hippocampal interneurons typically do not show discrete regions of elevated firing in an environment, such as seen in pyramidal cell place fields, they do exhibit significant spatial modulation (McNaughton et al., 1983a). Strong monosynaptic coupling between pyramidal neurons and nearby interneurons in the CA1 stratum pyramidale has been strongly implicated on the basis of significant, short-latency peaks in cross-correlogram plots (Csicsvari et al., 1998). Furthermore, interneurons receiving a putative monosynaptic connection from a simultaneously recorded pyramidal cell appear to inherit the spatial modulation of the latter (Marshall et al., 2002). Buzsaki and colleagues hypothesize that interneurons may also adopt the firing phase dynamics of their afferent place cells, which show a phase shift relative to the hippocampal theta rhythm as a rat passes through the place field ("phase precession"). This study confirms and extends the previous reports by showing that interneurons in the dorsal and middle hippocampus with putative monosynaptic connections with place cells recorded on the same tetrode share other properties with their pyramidal cell afferents, including the spatial scale of the place field of pyramidal cell, a characteristic of the septotemporal level of the hippocampus from which the cells are recorded, and the rate of phase precession, which is slower in middle regions. Furthermore, variations in pyramidal cell place field scale within each septotemporal level attributable to task variations are similarly associated with variations in interneuron place field scale. The available data strongly suggest that spatial selectivity of CA1 stratum pyramidale interneurons is inherited from a small cluster of local pyramidal cells and is not a consequence of spatially selective synaptic input from CA3 or other sources.

Grid cell firing may arise from interference of theta frequency membrane potential oscillations in single neurons

Intracellular recording and computational modelling suggest that interactions of subthreshold membrane potential oscillation frequency in different dendritic branches of entorhinal cortex stellate cells could underlie the functional coding of continuous dimensions of space and time. Among other things, these interactions could underlie properties of grid cell field spacing. The relationship between experimental data on membrane potential oscillation frequency (f) and grid cell field spacing (G) indicates a constant scaling factor H = fG. This constant scaling factor between temporal oscillation frequency and spatial periodicity provides a starting constraint that is used to derive the model of Burgess et al. (Hippocampus, 2007). This model provides a consistent quantitative link between single cell physiological properties and properties of spiking units in awake behaving animals. Further properties and predictions of this model about single cell and network physiological properties are analyzed. In particular, the model makes quantitative predictions about the change in membrane potential, single cell oscillation frequency, and network oscillation frequency associated with speed of movement, about the independence of single cell properties from network theta rhythm oscillations, and about the effect of variations in initial oscillatory phase on the pattern of grid cell firing fields. These same mechanisms of subthreshold oscillations may play a more general role in memory function, by providing a method for learning arbitrary time intervals in memory sequences.

Organization of hippocampal cell assemblies based on theta phase precession

The factors that control the spatial tuning of hippocampal neurons are incompletely understood, and there is no generally agreed upon definition of what constitutes a "place field". One factor that must be considered is the phenomenon of "phase precession". As a rat passes through the place field of a particular hippocampal neuron, its spikes shift to earlier phases of the theta rhythm. Except for the special cases discussed herein, the phase shift never exceeds 360 degrees. Moreover, under conditions in which place field sizes change dynamically, precession rate is tightly coupled with the place field size, suggesting that a single cycle of theta phase precession could be used to define unitary place field boundaries. Theta phase precession implies that the "cell assembly" of active hippocampal neurons changes systematically over the course of a single theta cycle. A given cell can exhibit more than one place field in a given environment, each field showing the same pattern of 360 degrees of phase precession. The existence of multiple fields implies that one cell can participate in multiple cell assemblies within the same environment. We show here that place fields, defined as a single cycle of phase precession, can overlap spatially, with the result that the cell fires with spikes clustered at two different phases over the theta cycles in which the fields overlap. Thus, the same neuron can participate in different cell assemblies within a single theta cycle.

Maintenance of multiple working memory items by temporal segmentation

Experimental work based on single cell recordings supports the hypothesis that working memory representations are retained by sustained neuronal firing. While this hypothesis can account for the maintenance of a single memory item, it remains unclear how multiple working memory items are represented. This account will discuss the possible physiological mechanism responsible for the maintenance of multiple working memory items including mechanisms based on sustained firing and synaptic encoding. The focus will be on temporal segmentation by phase encoding, namely the idea that several working memory items are activated sequentially at different points in time. It has been proposed that a mechanism of nested gamma (30-80 Hz) and theta (4-8 Hz) oscillations is responsible for controlling the reactivation of the memory list. This mechanism has been shown to be compatible with multiple behavioral findings on working memory such as the data from the Sternberg experiment. The theta/gamma mechanism has also received support from a large set of electrophysiological findings, however, more experimental work is required to further substantiate or falsify the model.

Frontal midline EEG dynamics during working memory

We show that during visual working memory, the electroencephalographic (EEG) process producing 5-7 Hz frontal midline theta (fmtheta) activity exhibits multiple spectral modes involving at least three frequency bands and a wide range of amplitudes. The process accounting for the fmtheta increase during working memory was separated from 71-channel data by clustering on time/frequency transforms of components returned by independent component analysis (ICA). Dipole models of fmtheta component scalp maps were consistent with their generation in or near dorsal anterior cingulate cortex. From trial to trial, theta power of fmtheta components varied widely but correlated moderately with theta power in other frontal and left temporal processes. The weak mean increase in frontal midline theta power with increasing memory load, produced entirely by the fmtheta components, largely reflected progressively stronger theta activity in a relatively small proportion of trials. During presentations of letter series to be memorized or ignored, fmtheta components also exhibited 12-15 Hz low-beta activity that was stronger during memorized than during ignored letter trials, independent of letter duration. The same components produced a brief 3-Hz burst 500 ms after onset of the Probe letter following each letter sequence. A new decomposition method, log spectral ICA, applied to normalized log time/frequency transforms of fmtheta component Memorize-letter trials, showed that their low-beta activity reflected harmonic energy in continuous, sharp-peaked theta wave trains as well as independent low-beta bursts. Possibly, the observed fmtheta process variability may index dynamic adjustments in medial frontal cortex to trial-specific behavioral context and task demands.

Conserving total synaptic weight ensures one-trial sequence learning of place fields in the hippocampus

The hippocampus plays a critical role in the rapid acquisition of information from a novel experience. Recent theoretical studies on the rat hippocampus have shown the possibility of behavioral sequence learning in a single traversal experience by theta phase coding. Specifically, previous work using computer simulations demonstrated that the extent of overlap among individual events of sequence and rat running velocity should be quantitatively incorporated into the learning rule to ensure one-trial sequence learning. These extents of overlap- and running velocity-dependent properties in the learning rule are called the input-dependent regulation of the learning rule. However, the biological meaning of such learning properties remains poorly understood. In this study, we quantitatively derive these learning properties with mathematical analyses. We further find that the input-dependent regulation of the learning rule allows maintenance of total synaptic weight over a given neuron during one-trial learning. Our results predict that a homeostatic plasticity mechanism should exist for conserving total synaptic weight on a rapid timescale.

Online formation of a hierarchical cognitive map for object-place association by theta phase coding

Object-place associative memory, the storage of object and place conjunctions based on a one-time experience, is hippocampal-dependent in humans. Theta phase precession, a type of neural dynamics observed in the rat hippocampus, has recently been suggested to serve a role in instantaneous memory formation based on a one-time experience, while its functional role in associating distinct types of information (object and place information) is unclear. In this study, we hypothesize that theta phase encoding with theta phase precession contributes to the storage of object-place associations. To examine this hypothesis, we propose a neural network model of the corticohippocampal system, including central-peripheral visual pathways and theta phase coding in the hippocampus. Memory storage computer experiments demonstrate that the hippocampal network successfully stores the object-place associations of a one-time experience. Interestingly, it is also found that a random visual input sequence results in a robust formation of asymmetric connections between objects and scenes instantaneously after a single trial. Furthermore, it is found that scene-object connections and scene-scene connections form a hierarchical network representing the spatial alignment of scenes and objects in the environment. Our findings indicate that the theta phase coding, as observed in the rat hippocampus, can facilitate the online memory storage of complex environments in humans as a hierarchical cognitive map.

Self-motion and the origin of differential spatial scaling along the septo-temporal axis of the hippocampus

Spatial scaling of place specific activity in the hippocampus varies systematically from the septal pole (high resolution) to the temporal pole (low resolution). Place fields get progressively larger, and the probability of observing a field in a given environment gets progressively smaller. It was previously found that decoupling movement in space from ambulation, by having the animal actively ride on a mobile platform, results in marked enlargement of the spatial scale factor in the dorsal hippocampus and a reduction in the increase in theta rhythm power with running speed, suggesting that a self-motion signal determines the spatial scale at which the hippocampal population vector updates. These results led to the hypothesis that the gain of the self-motion signal may vary systematically along the septo-temporal axis of the hippocampus. To test this hypothesis, EEG theta rhythm and ensembles of CA1 pyramidal cells and interneurons were recorded from the extreme dorsal and middle portions of the hippocampus. Pyramidal cell population vectors representing successive locations became decorrelated over substantially shorter distances in the dorsal than in the middle hippocampus. Dorsal pyramidal cells had smaller place fields, higher mean and peak firing rates, and higher intrinsic oscillation frequencies during track running than that of middle pyramidal cells. Both dorsal pyramidal cells and interneurons had more elevated mean rates during running, compared with rest, than that of the corresponding cell classes in the middle hippocampus, and both cell classes increased their rates more as a function of speed in the dorsal hippocampus.The amplitude, but not the frequency of fissure recorded theta rhythm, increased more as a function of running speed in the dorsal than in the middle hippocampus. We conclude that variation in the neuronal response to movement speed is the likely basis for the systematic variation in spatial scaling along the septo-temporal axis of the hippocampus.

Spike phase precession persists after transient intrahippocampal perturbation

Oscillatory spike timing in the hippocampus is regarded as a temporal coding mechanism for space, but the underlying mechanisms are poorly understood. To contrast the predictions of the different models of phase precession, we transiently turned off neuronal discharges for up to 250 ms and reset the phase of theta oscillations by stimulating the commissural pathway in rats. After recovery from silence, phase precession continued. The phase of spikes for the first theta cycle after the perturbation was more advanced than the phase of spikes for the last theta cycle just before the perturbation. These findings indicate that phase advancement that emerges within hippocampal circuitry may be updated at the beginning of each theta cycle by extrahippocampal inputs.

Dynamically detuned oscillations account for the coupled rate and temporal code of place cell firing

Firing of place cells in the exploring rat conveys doubly coded spatial information: both the rate of spikes and their timing relative to the phase of the ongoing field theta oscillation are correlated with the location of the animal. Specifically, the firing rate of a place cell waxes and wanes, while the timing of spikes precesses monotonically as the animal traverses the portion of the environment preferred by the cell. We propose a mechanism for the generation of this firing pattern that can be applied for place cells in all three hippocampal subfields and that encodes spatial information in the output of the cell without relying on topographical connections or topographical input. A single pyramidal cell was modeled so that the cell received rhythmic inhibition in phase with theta field potential oscillation on the soma and was excited on the dendrite with input depending on the speed of the rat. The dendrite sustained an intrinsic membrane potential oscillation, frequency modulated by its input. Firing probability of the cell was determined jointly by somatic and dendritic oscillations. Results were obtained on different levels of abstraction: a purely analytical derivation was arrived at, corroborated by numerical simulations of rate neurons, and an extension of these simulations to spiking neurons was also performed. Realistic patterns of rate and temporal coding emerged and were found to be inseparable. These results may have implications on the robustness of information coding in place cell firing and on the ways information is processed in structures downstream to the hippocampus.

Memory encoding by theta phase precession in the hippocampal network

Recent experimental evidence on spike-timing-dependent plasticity and on phase precession (i.e., the theta rhythm dependent firing of rat hippocampal cells) associates the contribution of phase precession to episodic memory. This article aims at clarifying the role of phase precession in memory storage. Computer simulations show that the memory storage in the behavioral timescale varies in timescale of the temporal sequence from half a second to several seconds. In contrast, the memory storage caused by traditional rate coding is restricted to the temporal sequence within 40 ms. During phase precession, memory storage of a single trial experience is possible, even in the presence of noise. It is therefore concluded that encoding by phase precession is appropriate for memory storage of the temporal sequence in the behavioral timescale.

Spiking neuron models with excitatory or inhibitory synaptic couplings and synchronization phenomena

We investigate synchronization phenomena in a system of two piecewise-linear-type model neurons with excitatory or inhibitory synaptic couplings. Employing the phase plane analysis and a singular perturbation approach to split the dynamics into slow and fast ones, we construct analytically the Poincaré map of the solution to the piecewise-linear equations. We investigate conditions for the occurrence of synchronized oscillations of in phase as well as of antiphase in terms of parameters representing the strength of the synaptic coupling and the decaying relaxation rate of the synaptic dynamics. We present the results of numerical simulations that agree with our theoretical ones.

Role of experience and oscillations in transforming a rate code into a temporal code

In the vast majority of brain areas, the firing rates of neurons, averaged over several hundred milliseconds to several seconds, can be strongly modulated by, and provide accurate information about, properties of their inputs. This is referred to as the rate code. However, the biophysical laws of synaptic plasticity require precise timing of spikes over short timescales (<10 ms). Hence it is critical to understand the physiological mechanisms that can generate precise spike timing in vivo, and the relationship between such a temporal code and a rate code. Here we propose a mechanism by which a temporal code can be generated through an interaction between an asymmetric rate code and oscillatory inhibition. Consistent with the predictions of our model, the rate and temporal codes of hippocampal pyramidal neurons are highly correlated. Furthermore, the temporal code becomes more robust with experience. The resulting spike timing satisfies the temporal order constraints of hebbian learning. Thus, oscillations and receptive field asymmetry may have a critical role in temporal sequence learning.

Bimodality of theta phase precession in hippocampal place cells in freely running rats

The firing of hippocampal principal cells in freely running rats exhibits a progressive phase retardation as the animal passes through a cell's "place" field. This "phase precession" is more complex than a simple linear shift of phase with position. In the present paper, phase precession is quantitatively analyzed by fitting multiple (1-3) normal probability density functions to the phase versus position distribution of spikes in rats making repeated traversals of the place fields. The parameters were estimated by the Expectation Maximization method. Three data sets including CA1 and DG place cells were analyzed. Although the phase-position distributions vary among different cells and regions, this complexity is well described by a superposition of two normal distribution functions, suggesting that the firing behavior consists of two components. This conclusion is supported by the existence of two distinct maxima in the mean spike density in the phase versus position plane. In one component, firing phase shifts over a range of about 180 degrees. The second component, which occurs near the end of the traversal of the place field, exhibits a low correlation between phase and position and is anti-phase with the phase-shift component. The functional implications of the two components are discussed with respect to their possible contribution to learning and memory mechanisms.

Phase precession and phase-locking of hippocampal pyramidal cells

We propose that the activity patterns of CA3 hippocampal pyramidal cells in freely running rats can be described as a temporal phenomenon, where the timing of bursts is modulated by the animal's running speed. With this hypothesis, we explain why pyramidal cells fire in specific spatial locations, and how place cells phase-precess with respect to the EEG theta rhythm for rats running on linear tracks. We are also able to explain why wheel cells phase-lock with respect to the theta rhythm for rats running in a wheel. Using biophysically minimal models of neurons, we show how the same network of neurons displays these activity patterns. The different rhythms are the result of inhibition being used in different ways by the system. The inhibition is produced by anatomically and physiologically diverse types of interneurons, whose role in controlling the firing patterns of hippocampal cells we analyze. Each firing pattern is characterized by a different set of functional relationships between network elements. Our analysis suggests a way to understand these functional relationships and transitions between them.

Summation of spatiotemporal input patterns in leaky integrate-and-fire neurons: application to neurons in the cochlear nucleus receiving converging auditory nerve fiber input

The response of leaky integrate-and-fire neurons is analyzed for periodic inputs whose phases vary with their spatial location. The model gives the relationship between the spatial summation distance and the degree of phase locking of the output spikes (i.e., locking to the periodic stochastic inputs, measured by the synchronization index). The synaptic inputs are modeled as an inhomogeneous Poisson process, and the analysis is carried out in the Gaussian approximation. The model has been applied to globular bushy cells of the cochlear nucleus, which receive converging inputs from auditory nerve fibers that originate at neighboring sites in the cochlea. The model elucidates the roles played by spatial summation and coincidence detection, showing how synchronization decreases with an increase in both frequency and spatial spread of inputs. It also shows under what conditions an enhancement of synchronization of the output relative to the input takes place.

The hippocampal debate: are we asking the right questions?

For years, the debate has been: "Is the hippocampus the cognitive map?" or "Is the hippocampus the core of memory?" These two hypotheses derived their original power from two key experiments--the cognitive map theory from the remarkable spatial correlates seen in recordings of hippocampal pyramidal cells and the memory theory from the profound amnesias seen in the patient H.M. Both of these key experiments have been reinterpreted over the years: hippocampal cells are correlated with much more than place and H.M. is missing much more than just his hippocampus. However, both theories are still debated today. The hippocampus clearly plays a role in both navigation and memory processing. The question that must be addressed is rather: "What is the role played by the hippocampus in the navigation and memory systems?" By looking at the navigation system as a whole, one can identify the major role played by the hippocampus as correcting for accumulation errors that occur within idiothetic navigation systems. This is most clearly experimentally evident as reorientation when an animal is lost. Carrying this over to a more general process, this becomes a role of recalling a context, bridging a contextual gap, or, in other words, it becomes a form of recognition memory. I will review recent experimental data which seems to support this theory over the more general spatial or memory theories traditionally applied to hippocampus.

New excitement in cognitive space: between place cells and spatial memory

Hippocampal principal neurons-'place cells'-exhibit location-specific firing. Recent work addresses the link between place cell activity and hippocampal memory function. New tasks that challenge spatial memory allow recording from single neurons, as well as ensembles of neurons, during memory computations, and insights into the cellular mechanisms of spatial memory are beginning to emerge.

Neuronal dynamics of predictive coding

A critical task of the central nervous system is to learn causal relationships between stimuli to anticipate events in the future, such as the position of a moving prey or predator. What are the neuronal phenomena underlying anticipation? In this article, I review recent results in hippocampal electrophysiology that shed light on this issue. It is shown that hippocampal spatial receptive fields show large and rapid anticipatory changes in their firing characteristics. These changes are experience- and environment-dependent and can be explained by a computational model based on NMDA-dependent synaptic plasticity during behavior. Striking similarities between the anticipatory network dynamics of widely different neural circuits, such as the hippocampus and primary visual cortex, are discussed. These experimental and theoretical results indicate how the microscopic laws of synaptic plasticity give rise to emergent anticipatory properties of receptive fields and behavior.

Neural mechanisms for generating rate and temporal codes in model CA3 pyramidal cells

The effect of synaptic inhibition on burst firing of a two-compartment model of a CA3 pyramidal cell is considered. We show that, depending on its timing, a short dose of fast decaying synaptic inhibition can either delay or advance the timing of firing of subsequent bursts. Moreover, increasing the strength of the inhibitory input is shown to modulate the burst profile from a full complex burst, to a burst with multiple spikes, to single spikes. We additionally show how slowly decaying inhibitory input can be used to synchronize a network of pyramidal cells. Implications for the phase precession phenomenon of hippocampal place cells and for the generation of temporal and rate codes are discussed.

Role of synaptic delay in organizing the behavior of networks of self-inhibiting neurons

We consider a pair of mutually coupled inhibitory neurons in which each neuron is also self-inhibitory. We show that the size of the synaptic delay determines the existence and stability of solutions. For small delays, there is no synchronous solution, but a stable antiphase and a stable on-state solution. For long delays, only the synchronous solution is stable. For intermediate delays, either the antiphase or synchronous solutions are stable. In contrast to prior work, for stability of synchrony, we only require the existence of a single slow process.