The Firing Rate Speed Code of Entorhinal Speed Cells Differs across Behaviorally Relevant Time Scales and Does Not Depend on Medial Septum Inputs

The influence of emotion on temporal context models

Temporal context models (TCMs) have been influential in understanding episodic memory and its neural underpinnings. Recently, TCMs have been extended to explain emotional memory effects, one of the most clinically important findings in the field of memory research. This review covers recent advances in hypotheses for the neural representation of spatiotemporal context through the lens of TCMs, including their ability to explain the influence of emotion on episodic and temporal memory. In recent years, simplifying assumptions of "classical" TCMs - with exponential trace decay and the mechanism by which temporal context is recovered - have become increasingly clear. The review also outlines how recent advances could be incorporated into a future TCM, beyond classical assumptions, to integrate emotional modulation.

A Continuous Attractor Model with Realistic Neural and Synaptic Properties Quantitatively Reproduces Grid Cell Physiology

Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize the wealth of cellular properties from Hippocampome.org to study neural mechanisms of spatial coding with a spiking continuous attractor network model of medial entorhinal cortex circuit activity. The primary goal was to investigate if adding such realistic constraints could produce firing patterns similar to those measured in real neurons. Biological characteristics included in the work are excitability, connectivity, and synaptic signaling of neuron types defined primarily by their axonal and dendritic morphologies. We investigate the spiking dynamics in specific neuron types and the synaptic activities between groups of neurons. Modeling the rodent hippocampal formation keeps the simulations to a computationally reasonable scale while also anchoring the parameters and results to experimental measurements. Our model generates grid cell activity that well matches the spacing, size, and firing rates of grid fields recorded in live behaving animals from both published datasets and new experiments performed for this study. Our simulations also recreate different scales of those properties, e.g., small and large, as found along the dorsoventral axis of the medial entorhinal cortex. Computational exploration of neuronal and synaptic model parameters reveals that a broad range of neural properties produce grid fields in the simulation. These results demonstrate that the continuous attractor network model of grid cells is compatible with a spiking neural network implementation sourcing data-driven biophysical and anatomical parameters from Hippocampome.org. The software is released as open source to enable broad community reuse and encourage novel applications.

Spatial periodicity in grid cell firing is explained by a neural sequence code of 2-D trajectories

Spatial periodicity in grid cell firing has been interpreted as a neural metric for space providing animals with a coordinate system in navigating physical and mental spaces. However, the specific computational problem being solved by grid cells has remained elusive. Here, we provide mathematical proof that spatial periodicity in grid cell firing is the only possible solution to a neural sequence code of 2-D trajectories and that the hexagonal firing pattern of grid cells is the most parsimonious solution to such a sequence code. We thereby provide a teleological cause for the existence of grid cells and reveal the underlying nature of the global geometric organization in grid maps as a direct consequence of a simple local sequence code. A sequence code by grid cells provides intuitive explanations for many previously puzzling experimental observations and may transform our thinking about grid cells.

Optogenetic Silencing of Medial Septal GABAergic Neurons Disrupts Grid Cell Spatial and Temporal Coding in the Medial Entorhinal Cortex

The hippocampus and medial entorhinal cortex (MEC) form a cognitive map that facilitates spatial navigation. As part of this map, MEC grid cells fire in a repeating hexagonal pattern across an environment. This grid pattern relies on inputs from the medial septum (MS). The MS, and specifically its GABAergic neurons, are essential for theta rhythm oscillations in the entorhinal-hippocampal network, however, it is unknown if this subpopulation is also essential for grid cell function. To investigate this, we used optogenetics to inhibit MS-GABAergic neurons during grid cell recordings. We found that MS-GABAergic inhibition disrupted grid cell spatial periodicity both during optogenetic inhibition and during short 30-second recovery periods. Longer recovery periods of 60 seconds between the optogenetic inhibition periods allowed for the recovery of grid cell spatial firing. Grid cell temporal coding was also disrupted, as observed by a significant attenuation of theta phase precession. Together, these results demonstrate that MS-GABAergic neurons are critical for grid cell spatial and temporal coding in the MEC.

Temporal dynamics of cholinergic activity in the septo-hippocampal system

Cholinergic projection neurons in the medial septum and diagonal band of Broca are the major source of cholinergic modulation of hippocampal circuit functions that support neural coding of location and running speed. Changes in cholinergic modulation are known to correlate with changes in brain states, cognitive functions, and behavior. However, whether cholinergic modulation can change fast enough to serve as a potential speed signal in hippocampal and parahippocampal cortices and whether the temporal dynamics in such a signal depend on the presence of visual cues remain unknown. In this study, we use a fiber-photometric approach to quantify the temporal dynamics of cholinergic activity in freely moving mice as a function of the animal's movement speed and visual cues. We show that the population activity of cholinergic neurons in the medial septum and diagonal band of Broca changes fast enough to be aligned well with changes in the animal's running speed and is strongly and linearly correlated to the logarithm of the animal's running speed. Intriguingly, the cholinergic modulation remains strongly and linearly correlated to the speed of the animal's neck movements during periods of stationary activity. Furthermore, we show that cholinergic modulation is unaltered during darkness. Lastly, we identify rearing, a stereotypic behavior where the mouse stands on its hindlimbs to scan the environment from an elevated perspective, is associated with higher cholinergic activity than expected from neck movements on the horizontal plane alone. Taken together, these data show that temporal dynamics in the cholinergic modulation of hippocampal circuits are fast enough to provide a potential running speed signal in real-time. Moreover, the data show that cholinergic modulation is primarily a function of the logarithm of the animal's movement speed, both during locomotion and during stationary activity, with no significant interaction with visual inputs. These data advance our understanding of temporal dynamics in cholinergic modulation of hippocampal circuits and their functions in the context of neural coding of location and running speed.

Microcircuits for spatial coding in the medial entorhinal cortex

The hippocampal formation is critically involved in learning and memory and contains a large proportion of neurons encoding aspects of the organism's spatial surroundings. In the medial entorhinal cortex (MEC), this includes grid cells with their distinctive hexagonal firing fields as well as a host of other functionally defined cell types including head direction cells, speed cells, border cells, and object-vector cells. Such spatial coding emerges from the processing of external inputs by local microcircuits. However, it remains unclear exactly how local microcircuits and their dynamics within the MEC contribute to spatial discharge patterns. In this review we focus on recent investigations of intrinsic MEC connectivity, which have started to describe and quantify both excitatory and inhibitory wiring in the superficial layers of the MEC. Although the picture is far from complete, it appears that these layers contain robust recurrent connectivity that could sustain the attractor dynamics posited to underlie grid pattern formation. These findings pave the way to a deeper understanding of the mechanisms underlying spatial navigation and memory.

Adaptive integration of self-motion and goals in posterior parietal cortex

Rats readily switch between foraging and more complex navigational behaviors such as pursuit of other rats or prey. These tasks require vastly different tracking of multiple behaviorally significant variables including self-motion state. To explore whether navigational context modulates self-motion tracking, we examined self-motion tuning in posterior parietal cortex neurons during foraging versus visual target pursuit. Animals performing the pursuit task demonstrate predictive processing of target trajectories by anticipating and intercepting them. Relative to foraging, pursuit yields multiplicative gain modulation of self-motion tuning and enhances self-motion state decoding. Self-motion sensitivity in parietal cortex neurons is, on average, history dependent regardless of behavioral context, but the temporal window of self-motion integration extends during target pursuit. Finally, many self-motion-sensitive neurons conjunctively track the visual target position relative to the animal. Thus, posterior parietal cortex functions to integrate the location of navigationally relevant target stimuli into an ongoing representation of past, present, and future locomotor trajectories.

Functional network topography of the medial entorhinal cortex

The investigation of the topographic organization of spatially coding cell types in the medial entorhinal cortex (MEC) has so far been held back by the lack of appropriate tools that enable the precise recording of both the anatomical location and activity of large populations of cells while animals forage in open environments. In this study, we use the newest generation of head-mounted, miniaturized two-photon microscopes to image grid, head-direction, border, as well as object-vector cells in MEC and neighboring parasubiculum within the same animals. The majority of cell types were intermingled, but grid and object-vector cells exhibited little overlap. The results have implications for network models of spatial coding.

The medial entorhinal cortex (MEC) creates a map of local space, based on the firing patterns of grid, head-direction (HD), border, and object-vector (OV) cells. How these cell types are organized anatomically is debated. In-depth analysis of this question requires collection of precise anatomical and activity data across large populations of neurons during unrestrained behavior, which neither electrophysiological nor previous imaging methods fully afford. Here, we examined the topographic arrangement of spatially modulated neurons in the superficial layers of MEC and adjacent parasubiculum using miniaturized, portable two-photon microscopes, which allow mice to roam freely in open fields. Grid cells exhibited low levels of co-occurrence with OV cells and clustered anatomically, while border, HD, and OV cells tended to intermingle. These data suggest that grid cell networks might be largely distinct from those of border, HD, and OV cells and that grid cells exhibit strong coupling among themselves but weaker links to other cell types.

Optogenetic suppression of the medial septum impairs working memory maintenance

Spatial working memory (SWM) is the ability to encode, maintain, and retrieve spatial information over a temporal gap, and relies on a network of structures including the medial septum (MS), which provides critical input to the hippocampus. Although the role of the MS in SWM is well-established, up until recently, we have been unable to use temporally precise circuit manipulation techniques to examine the specific role of the MS in SWM, particularly to distinguish between encoding, maintenance, and retrieval. Here, we test the hypothesis that the MS supports the maintenance of spatial information over a temporal gap using precisely timed optogenetic suppression delivered during specific portions of three different tasks, two of which rely on SWM and one that does not. In experiment 1, we found that MS optogenetic suppression impaired choice accuracy of a SWM dependent conditional discrimination task. Moreover, this deficit was only observed when MS suppression was delivered during the cue-sampling, but not the cue-retrieval, portion of the trial. There was also no deficit when MS neurons were optogenetically suppressed as rats performed a SWM-independent variant of the task. In experiment 2, we tested whether MS suppression affected choice accuracy on a delayed nonmatch to position (DNMP) task when suppression was limited to the sample, delay, and choice phases of the task. We found that MS suppression delivery during the delay phase of the DNMP task, but not during the sample or choice phases, impaired choice accuracy. Our results collectively suggest that the MS plays an important role in SWM by maintaining task-relevant information over a temporal delay.

Spiking Neural Networks and Hippocampal Function: A Web-Accessible Survey of Simulations, Modeling Methods, and Underlying Theories

Computational modeling has contributed to hippocampal research in a wide variety of ways and through a large diversity of approaches, reflecting the many advanced cognitive roles of this brain region. The intensively studied neuron type circuitry of the hippocampus is a particularly conducive substrate for spiking neural models. Here we present an online knowledge base of spiking neural network simulations of hippocampal functions. First, we overview theories involving the hippocampal formation in subjects such as spatial representation, learning, and memory. Then we describe an original literature mining process to organize published reports in various key aspects, including: (i) subject area (e.g., navigation, pattern completion, epilepsy); (ii) level of modeling detail (Hodgkin-Huxley, integrate-and-fire, etc.); and (iii) theoretical framework (attractor dynamics, oscillatory interference, self-organizing maps, and others). Moreover, every peer-reviewed publication is also annotated to indicate the specific neuron types represented in the network simulation, establishing a direct link with the Hippocampome.org portal. The web interface of the knowledge base enables dynamic content browsing and advanced searches, and consistently presents evidence supporting every annotation. Moreover, users are given access to several types of statistical reports about the collection, a selection of which is summarized in this paper. This open access resource thus provides an interactive platform to survey spiking neural network models of hippocampal functions, compare available computational methods, and foster ideas for suitable new directions of research.

A Brainstem Locomotor Circuit Drives the Activity of Speed Cells in the Medial Entorhinal Cortex

Locomotion activates an array of sensory inputs that may help build the self-position map of the medial entorhinal cortex (MEC). In this map, speed-coding neurons are thought to dynamically update representations of the animal’s position. A possible origin for the entorhinal speed signal is the mesencephalic locomotor region (MLR), which is critically involved in the activation of locomotor programs. Here, we describe, in rats, a circuit connecting the pedunculopontine tegmental nucleus (PPN) of the MLR to the MEC via the horizontal limb of the diagonal band of Broca (HDB). At each level of this pathway, locomotion speed is linearly encoded in neuronal firing rates. Optogenetic activation of PPN cells drives locomotion and modulates activity of speed-modulated neurons in HDB and MEC. Our results provide evidence for a pathway by which brainstem speed signals can reach cortical structures implicated in navigation and higher-order dynamic representations of space.

•

A speed-coding multisynaptic circuit connects PPN to MEC via HDB

•

Each level of the PPN-HDB-MEC pathway contains cells with linear speed coding

•

Optogenetic stimulation of PPN elicits activity in HDB and MEC speed cells

•

In MEC, locomotor inputs from PPN mainly target speed-modulated interneurons

Time to put the mammillothalamic pathway into context

The medial diencephalon, in particular the mammillary bodies and anterior thalamic nuclei, has long been linked to memory and amnesia. The mammillary bodies provide a dense input into the anterior thalamic nuclei, via the mammillothalamic tract. In both animal models, and in patients, lesions of the mammillary bodies, mammillothalamic tract and anterior thalamic nuclei all produce severe impairments in temporal and contextual memory, yet it is uncertain why these regions are critical. Mounting evidence from electrophysiological and neural imaging studies suggests that mammillothalamic projections exercise considerable distal influence over thalamo-cortical and hippocampo-cortical interactions. Here, we outline how damage to the mammillary body-anterior thalamic axis, in both patients and animal models, disrupts behavioural performance on tasks that relate to contextual ("where") and temporal ("when") processing. Focusing on the medial mammillary nuclei as a possible 'theta-generator' (through their interconnections with the ventral tegmental nucleus of Gudden) we discuss how the mammillary body-anterior thalamic pathway may contribute to the mechanisms via which the hippocampus and neocortex encode representations of experience.

Effects of visual inputs on neural dynamics for coding of location and running speed in medial entorhinal cortex

Neuronal representations of spatial location and movement speed in the medial entorhinal cortex during the ‘active’ theta state of the brain are important for memory-guided navigation and rely on visual inputs. However, little is known about how visual inputs change neural dynamics as a function of running speed and time. By manipulating visual inputs in mice, we demonstrate that changes in spatial stability of grid cell firing correlate with changes in a proposed speed signal by local field potential theta frequency. In contrast, visual inputs do not alter the running speed-dependent gain in neuronal firing rates. Moreover, we provide evidence that sensory inputs other than visual inputs can support grid cell firing, though less accurately, in complete darkness. Finally, changes in spatial accuracy of grid cell firing on a 10 s time scale suggest that grid cell firing is a function of velocity signals integrated over past time.

A temporal record of the past with a spectrum of time constants in the monkey entorhinal cortex

Episodic memory is believed to be intimately related to our experience of the passage of time. Indeed, neurons in the hippocampus and other brain regions critical to episodic memory code for the passage of time at a range of timescales. The origin of this temporal signal, however, remains unclear. Here, we examined temporal responses in the entorhinal cortex of macaque monkeys as they viewed complex images. Many neurons in the entorhinal cortex were responsive to image onset, showing large deviations from baseline firing shortly after image onset but relaxing back to baseline at different rates. This range of relaxation rates allowed for the time since image onset to be decoded on the scale of seconds. Further, these neurons carried information about image content, suggesting that neurons in the entorhinal cortex carry information about not only when an event took place but also, the identity of that event. Taken together, these findings suggest that the primate entorhinal cortex uses a spectrum of time constants to construct a temporal record of the past in support of episodic memory.

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

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

Cell type, sub-region, and layer-specific speed representation in the hippocampal-entorhinal circuit

It has been hypothesised that speed information, encoded by ‘speed cells’, is important for updating spatial representation in the hippocampus and entorhinal cortex to reflect ongoing self-movement during locomotion. However, systematic characterisation of speed representation is still lacking. In this study, we compared the speed representation of distinct cell types across sub-regions/layers in the dorsal hippocampus and medial entorhinal cortex of rats during exploration. Our results indicate that the preferred theta phases of individual neurons are correlated with positive/negative speed modulation and a temporal shift of speed representation in a sub-region/layer and cell type-dependent manner. Most speed cells located in entorhinal cortex layer 2 represented speed prospectively, whereas those in the CA1 and entorhinal cortex layers 3 and 5 represented speed retrospectively. In entorhinal cortex layer 2, putative CA1-projecting pyramidal cells, but not putative dentate gyrus/CA3-projecting stellate cells, represented speed prospectively. Among the hippocampal interneurons, approximately one-third of putative dendrite-targeting (somatostatin-expressing) interneurons, but only a negligible fraction of putative soma-targeting (parvalbumin-expressing) interneurons, showed negative speed modulation. Putative parvalbumin-expressing CA1 interneurons and somatostatin-expressing CA3 interneurons represented speed more retrospectively than parvalbumin-expressing CA3 interneurons. These findings indicate that speed representation in the hippocampal-entorhinal circuit is cell-type, pathway, and theta-phase dependent.

Neurophysiological coding of space and time in the hippocampus, entorhinal cortex, and retrosplenial cortex

Neurophysiological recordings in behaving rodents demonstrate neuronal response properties that may code space and time for episodic memory and goal-directed behaviour. Here, we review recordings from hippocampus, entorhinal cortex, and retrosplenial cortex to address the problem of how neurons encode multiple overlapping spatiotemporal trajectories and disambiguate these for accurate memory-guided behaviour. The solution could involve neurons in the entorhinal cortex and hippocampus that show mixed selectivity, coding both time and location. Some grid cells and place cells that code space also respond selectively as time cells, allowing differentiation of time intervals when a rat runs in the same location during a delay period. Cells in these regions also develop new representations that differentially code the context of prior or future behaviour allowing disambiguation of overlapping trajectories. Spiking activity is also modulated by running speed and head direction, supporting the coding of episodic memory not as a series of snapshots but as a trajectory that can also be distinguished on the basis of speed and direction. Recent data also address the mechanisms by which sensory input could distinguish different spatial locations. Changes in firing rate reflect running speed on long but not short time intervals, and few cells code movement direction, arguing against path integration for coding location. Instead, new evidence for neural coding of environmental boundaries in egocentric coordinates fits with a modelling framework in which egocentric coding of barriers combined with head direction generates distinct allocentric coding of location. The egocentric input can be used both for coding the location of spatiotemporal trajectories and for retrieving specific viewpoints of the environment. Overall, these different patterns of neural activity can be used for encoding and disambiguation of prior episodic spatiotemporal trajectories or for planning of future goal-directed spatiotemporal trajectories.

The Role of Hierarchical Dynamical Functions in Coding for Episodic Memory and Cognition

Behavioral research in human verbal memory function led to the initial definition of episodic memory and semantic memory. A complete model of the neural mechanisms of episodic memory must include the capacity to encode and mentally reconstruct everything that humans can recall from their experience. This article proposes new model features necessary to address the complexity of episodic memory encoding and recall in the context of broader cognition and the functional properties of neurons that could contribute to this broader scope of memory. Many episodic memory models represent individual snapshots of the world with a sequence of vectors, but a full model must represent complex functions encoding and retrieving the relations between multiple stimulus features across space and time on multiple hierarchical scales. Episodic memory involves not only the space and time of an agent experiencing events within an episode but also features shown in neurophysiological data such as coding of speed, direction, boundaries, and objects. Episodic memory includes not only a spatio-temporal trajectory of a single agent but also segments of spatio-temporal trajectories for other agents and objects encountered in the environment consistent with data on encoding the position and angle of sensory features of objects and boundaries. We will discuss potential interactions of episodic memory circuits in the hippocampus and entorhinal cortex with distributed neocortical circuits that must represent all features of human cognition.