Distinct hippocampal network states support theta phase precession and theta sequences in CA1

The hippocampus likely uses temporal coding to represent complex memories via mechanisms such as theta phase precession and theta sequences. Theta sequences are rapid sweeps of spikes from multiple place cells, encoding past or planned trajectories or non-spatial information. Phase precession, the correlation between a place cell's theta firing phase and animal position has been suggested to facilitate sequence emergence. We find that CA1 phase precession varies strongly across cells and environmental contingencies. Phase precession depends on the CA1 network state, and is only present when the medium gamma oscillation (60-90 Hz, linked to Entorhinal inputs) dominates. Conversely, theta sequences are most evident for non-precessing cells or with leading slow gamma (20-45 Hz, linked to CA3 inputs). These results challenge the view that phase precession is the mechanism underlying the emergence of theta sequences and point at a 'dual network states' model for hippocampal temporal code, potentially supporting merging of memory and exogenous information in CA1.

Directional Tuning of Phase Precession Properties in the Hippocampus

Running direction in the hippocampus is encoded by rate modulations of place field activity but also by spike timing correlations known as theta sequences. Whether directional rate codes and the directionality of place field correlations are related, however, has so far not been explored and therefore the nature of how directional information is encoded in the cornu ammonis remains unresolved. Here, using a previously published dataset that contains the spike activity of rat hippocampal place cells in the CA1, CA2 and CA3 subregions during free foraging of male Long-Evans rats in a 2D environment, we found that rate and spike timing codes are related. Opposite to a place field's preferred firing rate direction spikes are more likely to undergo theta phase precession and, hence, more strongly impact paired correlations. Furthermore, we identified a subset of field pairs whose theta correlations are intrinsic in that they maintain the same firing order when the running direction is reversed. Both effects are associated with differences in theta phase distributions, and are more prominent in CA3 than CA1. We thus hypothesize that intrinsic spiking is most prominent when the directionally modulated sensory-motor drive of hippocampal firing rates is minimal, suggesting that extrinsic and intrinsic sequences contribute to phase precession as two distinct mechanisms.

Neuronal sequences during theta rely on behavior-dependent spatial maps

Navigation through space involves learning and representing relationships between past, current and future locations. In mammals, this might rely on the hippocampal theta phase code, where in each cycle of the theta oscillation, spatial representations provided by neuronal sequences start behind the animal's true location and then sweep forward. However, the exact relationship between theta phase, represented position and true location remains unclear and even paradoxical. Here, we formalize previous notions of 'spatial' or 'temporal' theta sweeps that have appeared in the literature. We analyze single-cell and population variables in unit recordings from rat CA1 place cells and compare them to model simulations based on each of these schemes. We show that neither spatial nor temporal sweeps quantitatively accounts for how all relevant variables change with running speed. To reconcile these schemes with our observations, we introduce 'behavior-dependent' sweeps, in which theta sweep length and place field properties, such as size and phase precession, vary across the environment depending on the running speed characteristic of each location. These behavior-dependent spatial maps provide a structured heterogeneity that is essential for understanding the hippocampal code.

Disorganization of Oscillatory Activity in Animal Models of Schizophrenia

Schizophrenia is a chronic, debilitating disorder with diverse symptomatology, including disorganized cognition and behavior. Despite considerable research effort, we have only a limited understanding of the underlying brain dysfunction. In this article, we review the potential role of oscillatory circuits in the disorder with a particular focus on the hippocampus, a region that encodes sequential information across time and space, as well as the frontal cortex. Several mechanistic explanations of schizophrenia propose that a loss of oscillatory synchrony between and within these brain regions may underlie some of the symptoms of the disorder. We describe how these oscillations are affected in several animal models of schizophrenia, including models of genetic risk, maternal immune activation (MIA) models, and models of NMDA receptor hypofunction. We then critically discuss the evidence for disorganized oscillatory activity in these models, with a focus on gamma, sharp wave ripple, and theta activity, including the role of cross-frequency coupling as a synchronizing mechanism. Finally, we focus on phase precession, which is an oscillatory phenomenon whereby individual hippocampal place cells systematically advance their firing phase against the background theta oscillation. Phase precession is important because it allows sequential experience to be compressed into a single 120 ms theta cycle (known as a ‘theta sequence’). This time window is appropriate for the induction of synaptic plasticity. We describe how disruption of phase precession could disorganize sequential processing, and thereby disrupt the ordered storage of information. A similar dysfunction in schizophrenia may contribute to cognitive symptoms, including deficits in episodic memory, working memory, and future planning.

Orthogonal representation of task-related information in theta phase-based multiple place fields of single units in the subiculum

The subiculum is positioned at a critical juncture at the interface of the hippocampus with the rest of the brain. However, the exact roles of the subiculum in most hippocampal-dependent memory tasks remain largely unknown. One obstacle to make analytical comparisons of neural firing patterns between the subiculum and hippocampal CA1 is the broad firing fields of the subicular cells. Here, we used spiking phases in relation to theta rhythm to parse the broad firing field of a subicular neuron into multiple subfields to find the unique functional contribution of the subiculum while male rats performed a hippocampal-dependent visual scene memory task. Some of the broad firing fields of the subicular neurons were successfully divided into multiple subfields by using the theta-phase precession cycle. The resulting phase-based fields in the subiculum were more similar to those in CA1 in terms of the field size and phase-precession strength. The new method significantly improved the detection of task-relevant information in subicular cells without affecting the information content represented by CA1 cells. Notably, multiple fields of a single subicular neuron, unlike those in the CA1, could carry heterogeneous task-related information such as visual context and choice response. Our findings suggest that the subicular cells integrate multiple task-related factors by using theta rhythm to associate environmental context with action.

Theta-phase dependent neuronal coding during sequence learning in human single neurons

The ability to maintain a sequence of items in memory is a fundamental cognitive function. In the rodent hippocampus, the representation of sequentially organized spatial locations is reflected by the phase of action potentials relative to the theta oscillation (phase precession). We investigated whether the timing of neuronal activity relative to the theta brain oscillation also reflects sequence order in the medial temporal lobe of humans. We used a task in which human participants learned a fixed sequence of pictures and recorded single neuron and local field potential activity with implanted electrodes. We report that spikes for three consecutive items in the sequence (the preferred stimulus for each cell, as well as the stimuli immediately preceding and following it) were phase-locked at distinct phases of the theta oscillation. Consistent with phase precession, spikes were fired at progressively earlier phases as the sequence advanced. These findings generalize previous findings in the rodent hippocampus to the human temporal lobe and suggest that encoding stimulus information at distinct oscillatory phases may play a role in maintaining sequential order in memory.

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

Music, like language, is characterized by hierarchically organized structure that unfolds over time. Music listening therefore requires not only the tracking of notes and beats but also internally constructing high-level musical structures or phrases and anticipating incoming contents. Unlike for language, mechanistic evidence for online musical segmentation and prediction at a structural level is sparse. We recorded neurophysiological data from participants listening to music in its original forms as well as in manipulated versions with locally or globally reversed harmonic structures. We discovered a low-frequency neural component that modulated the neural rhythms of beat tracking and reliably parsed musical phrases. We next identified phrasal phase precession, suggesting that listeners established structural predictions from ongoing listening experience to track phrasal boundaries. The data point to brain mechanisms that listeners use to segment continuous music at the phrasal level and to predict abstract structural features of music.

Learning spatio-temporal properties of hippocampal place cells

Hippocampal place cells have spatio-temporal properties: they generally respond to a single spatial position of a small environment; in addition, they also display a temporal property, the theta phase precession, namely that the phase of spiking relative to the theta wave shifts from the late phase to early phase as the animal crosses the place field. Grid cells in layer II of medial entorhinal cortex (MEC) also have spatio-temporal properties similar to hippocampal place cells, except that grid cells respond to multiple spatial locations that form a hexagonal pattern. Other non-grid spatial cells are also abundant in the entorhinal cortex (EC). EC is the upstream that projects strongly to the hippocampus, many EC-hippocampus models have been designed to explain how the spatial property of place cells emerges. However, there is no learning model explaining how the temporal properties of hippocampal place cells emerge from the EC input. A learning model is presented here based on non-negative sparse coding in which we show that the spatial and temporal properties of hippocampal place cells can be simultaneously learnt from EC input: both MEC grid cells and other EC spatial cells contribute to the spatial properties of hippocampal place cells while MEC grid cells contribute to the temporal properties of hippocampal place cells.