Hippocampal theta oscillations are slower in humans than in rodents: implications for models of spatial navigation and memory

The theta oscillation is a neuroscience enigma. When a rat runs through an environment, large-amplitude theta oscillations (4–10 Hz) reliably appear in the hippocampus''s electrical activity. The consistency of this pattern led to theta playing a central role in theories on the neural basis of mammalian spatial navigation and memory. However, in fact, hippocampal oscillations at 4–10 Hz are rare in humans and in some other species. This presents a challenge for theories proposing theta as an essential component of the mammalian brain, including models of place and grid cells. Here, I examine this issue by reviewing recent research on human hippocampal oscillations using direct brain recordings from neurosurgical patients. This work indicates that the human hippocampus does indeed exhibit rhythms that are functionally similar to theta oscillations found in rodents, but that these signals have a slower frequency of approximately 1–4 Hz. I argue that oscillatory models of navigation and memory derived from rodent data are relevant for humans, but that they should be modified to account for the slower frequency of the human theta rhythm.     

Continuous Attractor Network Model for Conjunctive Position-by-Velocity Tuning of Grid Cells

The spatial responses of many of the cells recorded in layer II of rodent medial entorhinal cortex (MEC) show a triangular grid pattern, which appears to provide an accurate population code for animal spatial position. In layer III, V and VI of the rat MEC, grid cells are also selective to head-direction and are modulated by the speed of the animal. Several putative mechanisms of grid-like maps were proposed, including attractor network dynamics, interactions with theta oscillations or single-unit mechanisms such as firing rate adaptation. In this paper, we present a new attractor network model that accounts for the conjunctive position-by-velocity selectivity of grid cells. Our network model is able to perform robust path integration even when the recurrent connections are subject to random perturbations.     

Models of place and grid cell firing and theta rhythmicity

Neuronal firing in the hippocampal formation (HF) of freely moving rodents shows striking examples of spatialorganization in the form of place, directional, boundary vector and grid cells. The firing of place and grid cells shows an intriguing form of temporal organization known as 'theta phase precession'. We review the mechanisms underlying theta phase precession of place cell firing, ranging from membrane potential oscillations to recurrent connectivity, and the relevant intra-cellular and extra-cellular data. We then consider the use of these models to explain the spatial structure of grid cell firing, and review the relevant intra-cellular and extra-cellular data. Finally, we consider the likely interaction between place cells, grid cells and boundary vector cells in estimating self-location as a compromise between path-integration and environmental information.     

Neuronal rebound spiking,resonance frequency and theta cycle skipping may contribute to grid cell firing in medial entorhinal cortex

Data show a relationship of cellular resonance and network oscillations in the entorhinal cortex to the spatial periodicity of grid cells. This paper presents a model that simulates the resonance and rebound spiking properties of entorhinal neurons to generate spatial periodicity dependent upon phasic input from medial septum. The model shows that a difference in spatial periodicity can result from a difference in neuronal resonance frequency that replicates data from several experiments. The model also demonstrates a functional role for the phenomenon of theta cycle skipping in the medial entorhinal cortex.     

Synchronized oscillations at alpha and theta frequencies in the lateral geniculate nucleus

In relaxed wakefulness, the EEG exhibits robust rhythms in the alpha band (8-13 Hz), which decelerate to theta (approximately 2-7 Hz) frequencies during early sleep. In animal models, these rhythms occur coherently with synchronized activity in the thalamus. However, the mechanisms of this thalamic activity are unknown. Here we show that, in slices of the lateral geniculate nucleus maintained in vitro, activation of the metabotropic glutamate receptor (mGluR) mGluR1a induces synchronized oscillations at alpha and theta frequencies that share similarities with thalamic alpha and theta rhythms recorded in vivo. These in vitro oscillations are driven by an unusual form of burst firing that is present in a subset of thalamocortical neurons and are synchronized by gap junctions. We propose that mGluR1a-induced oscillations are a potential mechanism whereby the thalamus promotes EEG alpha and theta rhythms in the intact brain.     

Locomotion-related oscillatory body movements at 6-12 Hz modulate the hippocampal theta rhythm

The hippocampal theta rhythm is required for accurate navigation and spatial memory but its relation to the dynamics of locomotion is poorly understood. We used miniature accelerometers to quantify with high temporal and spatial resolution the oscillatory movements associated with running in rats. Simultaneously, we recorded local field potentials in the CA1 area of the hippocampus. We report that when rats run their heads display prominent vertical oscillations with frequencies in the same range as the hippocampal theta rhythm (i.e., 6-12 Hz). In our behavioral set-up, rats run mainly with speeds between 50 and 100 cm/s. In this range of speeds, both the amplitude and frequency of the "theta" head oscillations were increasing functions of running speed, demonstrating that the head oscillations are part of the locomotion dynamics. We found evidence that these rhythmical locomotor dynamics interact with the neuronal activity in the hippocampus. The amplitude of the hippocampal theta rhythm depended on the relative phase shift with the head oscillations, being maximal when the two signals were in phase. Despite similarity in frequency, the head movements and LFP oscillations only displayed weak phase and frequency locking. Our results are consistent with that neurons in the CA1 region receive inputs that are phase locked to the head acceleration signal and that these inputs are integrated with the ongoing theta rhythm.     

Hippocampal theta-driving cells revealed by Granger causality

The two-dipole model of theta generation in hippocampal CA1 suggests that the inhibitory perisomatic theta dipole is generated by local GABAergic interneurons. Various CA1 interneurons fire preferentially at different theta phases, raising the question of how these theta-locked interneurons contribute to the generation of theta oscillations. We here recorded interneurons in the hippocampal CA1 area of freely behaving mice, and identified a unique subset of theta-locked interneurons by using the Granger causality approach. These cells fired in an extremely reliable theta-burst pattern at high firing rates (～90 Hz) during exploration and always locked to ascending phases of the theta waves. Among theta-locked interneurons we recorded, only these cells generated strong Granger causal influences on local field potential (LFP) signals within the theta band (4-12 Hz), and the influences were persistent across behavioral states. Our results suggest that this unique type of theta-locked interneurons serve as the local inhibitory theta dipole control cells in shaping hippocampal theta oscillations.     

Theta returns

Recent physiological studies have implicated theta - a high-amplitude 4-8 Hz oscillation that is prominent in rat hippocampus during locomotion, orienting and other voluntary behaviors - in synaptic plasticity, information coding and the function of working memory. Intracranial recordings from human cortex have revealed evidence of high-amplitude theta oscillations throughout the brain, including the neocortex. Although its specific role is largely unknown, the observation of human theta has begun to reveal an intriguing connection between brain oscillations and cognitive processes.     

Mechanisms of the regulation and functional significance of the theta rhythm. Roles of serotonergic and noradrenergic systems

The evidence for the role of serotonergic and noradrenergic effects on the septohippocampal theta oscillations obtained by the author and her colleagues are reviewed. Analysis of neuronal activity in the medial septal area or hippocampus and hippocampal EEG simultaneously recorded in awake rabbits exposed to different kinds of brainstem influences led to the following conclusions. 1. Serotonergic median raphe nucleus and noradrenergic locus ceruleus act as functional antagonists in theta regulation: the former structure restricts the theta rhythm generation, whereas the latter enhances this process. 2. Both transmitter systems control sensory reactions of septal and hippocampal neurons through up and down regulation of the theta activity. 3. When continuous theta activity induced by various experimental manipulations is recorded, responsiveness of septohippocampal neurons to sensory stimulation is strongly reduced. These findings provide support for the view that the theta oscillations act as an active filter in the information selection and registration. Interaction of different transmitter systems in the theta rhythm control as well as attention and memory is discussed.     

A computational study on altered theta-gamma coupling during learning and phase coding

There is considerable interest in the role of coupling between theta and gamma oscillations in the brain in the context of learning and memory. Here we have used a neural network model which is capable of producing coupling of theta phase to gamma amplitude firstly to explore its ability to reproduce reported learning changes and secondly to memory-span and phase coding effects. The spiking neural network incorporates two kinetically different GABA(A) receptor-mediated currents to generate both theta and gamma rhythms and we have found that by selective alteration of both NMDA receptors and GABA(A,slow) receptors it can reproduce learning-related changes in the strength of coupling between theta and gamma either with or without coincident changes in theta amplitude. When the model was used to explore the relationship between theta and gamma oscillations, working memory capacity and phase coding it showed that the potential storage capacity of short term memories, in terms of nested gamma-subcycles, coincides with the maximal theta power. Increasing theta power is also related to the precision of theta phase which functions as a potential timing clock for neuronal firing in the cortex or hippocampus.     

Theta oscillations decrease spike synchrony in the hippocampus and entorhinal cortex

Oscillations and synchrony are often used synonymously. However, oscillatory mechanisms involving both excitation and inhibition can generate non-synchronous yet coordinated firing patterns. Using simultaneous recordings from multiple layers of the entorhinal–hippocampal loop, we found that coactivation of principal cell pairs (synchrony) was lowest during exploration and rapid-eye-movement (REM) sleep, associated with theta oscillations, and highest in slow wave sleep. Individual principal neurons had a wide range of theta phase preference. Thus, while theta oscillations reduce population synchrony, they nevertheless coordinate the phase (temporal) distribution of neurons. As a result, multiple cell assemblies can nest within the period of the theta cycle.     

Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales,attention and oscillations

A neural model proposes how entorhinal grid cells and hippocampal place cells may develop as spatial categories in a hierarchy of self-organizing maps (SOMs). The model responds to realistic rat navigational trajectories by learning both grid cells with hexagonal grid firing fields of multiple spatial scales, and place cells with one or more firing fields, that match neurophysiological data about their development in juvenile rats. Both grid and place cells can develop by detecting, learning and remembering the most frequent and energetic co-occurrences of their inputs. The model''s parsimonious properties include: similar ring attractor mechanisms process linear and angular path integration inputs that drive map learning; the same SOM mechanisms can learn grid cell and place cell receptive fields; and the learning of the dorsoventral organization of multiple spatial scale modules through medial entorhinal cortex to hippocampus (HC) may use mechanisms homologous to those for temporal learning through lateral entorhinal cortex to HC (‘neural relativity’). The model clarifies how top-down HC-to-entorhinal attentional mechanisms may stabilize map learning, simulates how hippocampal inactivation may disrupt grid cells, and explains data about theta, beta and gamma oscillations. The article also compares the three main types of grid cell models in the light of recent data.     

Computational theories on the function of theta oscillations

Neural rhythms can be studied in terms of conditions for their generation, or in terms of their functional significance. The theta oscillation is a particularly prominent rhythm, reported to be present in many brain areas, and related to many important cognitive processes. The generating mechanisms of theta have extensively been studied and reviewed elsewhere; here we discuss ideas that have accumulated over the past decades on the computational roles it may subserve. Theories propose different aspects of theta oscillations as being relevant for their cognitive functions: limit cycle oscillations in neuronal firing rates, subthreshold membrane potential oscillations, periodic modulation of synaptic transmission and plasticity, and phase precession of hippocampal place cells. The relevant experimental data is briefly summarized in the light of these theories. Specific models proposing a function for theta in pattern recognition, memory, sequence learning and navigation are reviewed critically. Difficulties with testing and comparing alternative models are discussed, along with potentially important future research directions in the field.     

Simulation of the hippocampal theta rhythm

Centre of Theoretical and Computational Neuroscience, University of Plymouth, UK Basing on the hypothesis about the mechanisms of the theta rhythm generation, the article presents mathematical and computational models of theta activity in the hippocampus. The problem of the theta rhythm modeling is nontrivial because the slow theta oscillations (about 5 Hz) should be generated by a neural system composed of frequently firing neural populations. We studied a model of neural pacemakers in the septum. In this model, the pacemaker follows the frequency of the external signal if this frequency does not deviate too far from the natural frequency of the pacemaker, otherwise the pacemaker returns to the frequency of its own oscillations. These results are in agreement with the experimental records of medial septum neurons. Our model of the septal pacemaker of the theta rhythm is based on the hypothesis that the hippocampal theta appears as a result of the influence of the assemblies of neurons in the medial septum which are under control of pacemaker neurons. Though the model of the pacemaker satisfies many experimental facts, the synchronization of activity in different neural assemblies of the model is not as strong as it should be. Another model of the theta generation is based on the anatomical data about the existence of the inhibitory GABAergic loop between the medial septum and the hippocampus. This model shows stable oscillations at the frequency of the theta rhythm in a broad range of parameter values. It also provides explanation to the experimental data about the variation of the frequency and the amplitude of the theta rhythm under different external stimulations of the system. The role of the theta rhythm for information processing in the hippocampus is discussed.     

Smell-induced gamma oscillations in human olfactory cortex are required for accurate perception of odor identity

Studies of neuronal oscillations have contributed substantial insight into the mechanisms of visual, auditory, and somatosensory perception. However, progress in such research in the human olfactory system has lagged behind. As a result, the electrophysiological properties of the human olfactory system are poorly understood, and, in particular, whether stimulus-driven high-frequency oscillations play a role in odor processing is unknown. Here, we used direct intracranial recordings from human piriform cortex during an odor identification task to show that 3 key oscillatory rhythms are an integral part of the human olfactory cortical response to smell: Odor induces theta, beta, and gamma rhythms in human piriform cortex. We further show that these rhythms have distinct relationships with perceptual behavior. Odor-elicited gamma oscillations occur only during trials in which the odor is accurately perceived, and features of gamma oscillations predict odor identification accuracy, suggesting that they are critical for odor identity perception in humans. We also found that the amplitude of high-frequency oscillations is organized by the phase of low-frequency signals shortly following sniff onset, only when odor is present. Our findings reinforce previous work on theta oscillations, suggest that gamma oscillations in human piriform cortex are important for perception of odor identity, and constitute a robust identification of the characteristic electrophysiological response to smell in the human brain. Future work will determine whether the distinct oscillations we identified reflect distinct perceptual features of odor stimuli.

Intracranial recordings from human olfactory cortex reveal a characteristic spectrotemporal response to odors, including theta, beta and gamma oscillations, and show that high-frequency responses are critical for accurate perception of odors.     

Directional Theta Coherence in Prefrontal Cortical to Amygdalo-Hippocampal Pathways Signals Fear Extinction

Theta oscillations are considered crucial mechanisms in neuronal communication across brain areas, required for consolidation and retrieval of fear memories. One form of inhibitory learning allowing adaptive control of fear memory is extinction, a deficit of which leads to maladaptive fear expression potentially leading to anxiety disorders. Behavioral responses after extinction training are thought to reflect a balance of recall from extinction memory and initial fear memory traces. Therefore, we hypothesized that the initial fear memory circuits impact behavioral fear after extinction, and more specifically, that the dynamics of theta synchrony in these pathways signal the individual fear response. Simultaneous multi-channel local field and unit recordings were obtained from the infralimbic prefrontal cortex, the hippocampal CA1 and the lateral amygdala in mice. Data revealed that the pattern of theta coherence and directionality within and across regions correlated with individual behavioral responses. Upon conditioned freezing, units were phase-locked to synchronized theta oscillations in these pathways, characterizing states of fear memory retrieval. When the conditioned stimulus evoked no fear during extinction recall, theta interactions were directional with prefrontal cortical spike firing leading hippocampal and amygdalar theta oscillations. These results indicate that the directional dynamics of theta-entrained activity across these areas guide changes in appraisal of threatening stimuli during fear memory and extinction retrieval. Given that exposure therapy involves procedures and pathways similar to those during extinction of conditioned fear, one therapeutical extension might be useful that imposes artificial theta activity to prefrontal cortical-amygdalo-hippocampal pathways that mimics the directionality signaling successful extinction recall.     

Correlations and Functional Connections in a Population of Grid Cells

We study the statistics of spike trains of simultaneously recorded grid cells in freely behaving rats. We evaluate pairwise correlations between these cells and, using a maximum entropy kinetic pairwise model (kinetic Ising model), study their functional connectivity. Even when we account for the covariations in firing rates due to overlapping fields, both the pairwise correlations and functional connections decay as a function of the shortest distance between the vertices of the spatial firing pattern of pairs of grid cells, i.e. their phase difference. They take positive values between cells with nearby phases and approach zero or negative values for larger phase differences. We find similar results also when, in addition to correlations due to overlapping fields, we account for correlations due to theta oscillations and head directional inputs. The inferred connections between neurons in the same module and those from different modules can be both negative and positive, with a mean close to zero, but with the strongest inferred connections found between cells of the same module. Taken together, our results suggest that grid cells in the same module do indeed form a local network of interconnected neurons with a functional connectivity that supports a role for attractor dynamics in the generation of grid pattern.     

Patterns of coupled theta activity in amygdala-hippocampal-prefrontal cortical circuits during fear extinction

Signals related to fear memory and extinction are processed within brain pathways involving the lateral amygdala (LA) for formation of aversive stimulus associations, the CA1 area of the hippocampus for context-dependent modulation of these associations, and the infralimbic region of the medial prefrontal cortex (mPFC) for extinction processes. While many studies have addressed the contribution of each of these modules individually, little is known about their interactions and how they function as an integrated system. Here we show, by combining multiple site local field potential (LFP) and unit recordings in freely behaving mice in a fear conditioning paradigm, that theta oscillations may provide a means for temporally and functionally connecting these modules. Theta oscillations occurred with high specificity in the CA1-LA-mPFC network. Theta coupling increased between all areas during retrieval of conditioned fear, and declined during extinction learning. During extinction recall, theta coupling partly rebounded in LA-mPFC and CA1-mPFC, and remained at a low level in CA1-LA. Interfering with theta coupling through local electrical microstimulation in CA1-LA affected conditioned fear and extinction recall depending on theta phase. These results support the hypothesis that theta coupling provides a means for inter-areal coordination in conditioned behavioral responsiveness. More specifically, theta oscillations seem to contribute to a population code indicating conditioned stimuli during recall of fear memory before and after extinction.     

Traveling Theta Waves along the Entire Septotemporal Axis of the Hippocampus

A topographical relationship exists between the hippocampus-entorhinal cortex and the neocortex. However, it is not known how these anatomical connections are utilized during information exchange and behavior. We recorded theta oscillations along the entire extent of the septotemporal axis of the hippocampal CA1 pyramidal layer. While the frequency of theta oscillation remained same along the entire long axis, the amplitude and coherence between recording sites decreased from dorsal to ventral hippocampus (VH). Theta phase shifted monotonically with distance along the longitudinal axis, reaching ～180° between the septal and temporal poles. The majority of concurrently recorded units were phase-locked to the local field theta at all dorsoventral segments. The power of VH theta had only a weak correlation with locomotion velocity, and its amplitude varied largely independently from theta in the dorsal part. Thus, theta oscillations can temporally combine or segregate neocortical representations along the septotemporal axis of the hippocampus.     

Speech Rhythms and Multiplexed Oscillatory Sensory Coding in the Human Brain

Cortical oscillations are likely candidates for segmentation and coding of continuous speech. Here, we monitored continuous speech processing with magnetoencephalography (MEG) to unravel the principles of speech segmentation and coding. We demonstrate that speech entrains the phase of low-frequency (delta, theta) and the amplitude of high-frequency (gamma) oscillations in the auditory cortex. Phase entrainment is stronger in the right and amplitude entrainment is stronger in the left auditory cortex. Furthermore, edges in the speech envelope phase reset auditory cortex oscillations thereby enhancing their entrainment to speech. This mechanism adapts to the changing physical features of the speech envelope and enables efficient, stimulus-specific speech sampling. Finally, we show that within the auditory cortex, coupling between delta, theta, and gamma oscillations increases following speech edges. Importantly, all couplings (i.e., brain-speech and also within the cortex) attenuate for backward-presented speech, suggesting top-down control. We conclude that segmentation and coding of speech relies on a nested hierarchy of entrained cortical oscillations.