A structured scaffold underlies activity in the hippocampus

Place cells are believed to organize memory across space and time, inspiring the idea of the cognitive map. Yet unlike the structured activity in the associated grid and head-direction cells, they remain an enigma: their responses have been difficult to predict and are complex enough to be statistically well-described by a random process. Here we report one step toward the ultimate goal of understanding place cells well enough to predict their fields. Within a theoretical framework in which place fields are derived as a conjunction of external cues with internal grid cell inputs, we predict that even apparently random place cell responses should reflect the structure of their grid inputs and that this structure can be unmasked if probed in sufficiently large neural populations and large environments. To test the theory, we design experiments in long, locally featureless spaces to demonstrate that structured scaffolds undergird place cell responses. Our findings, together with other theoretical and experimental results, suggest that place cells build memories of external inputs by attaching them to a largely prespecified grid scaffold.

40 Hz Light Flicker Promotes Learning and Memory via Long Term Depression in Wild-Type Mice

Background: 40 Hz light flicker is a well-known non-invasive treatment that is thought to be effective in treating Alzheimer’s disease. However, the effects of 40 Hz visual stimulation on neural networks, synaptic plasticity, and learning and memory in wild-type animals remain unclear. Objective: We aimed to explore the impact of 40 Hz visual stimulation on synaptic plasticity, place cell, and learning and memory in wild-type mice. Methods: c-Fos+ cell distribution and in vivo electrophysiology was used to explore the effects of 40 Hz chronic visual stimulation on neural networks and neuroplasticity in wild-type mice. The character of c-Fos+ distribution in the brain and the changes of corticosterone levels in the blood were used to investigate the state of animal. Place cell analysis and novel location test were utilized to examine the effects of 40 Hz chronic visual stimulation on learning and memory in wild-type mice. Results: We found that 40 Hz light flicker significantly affected many brain regions that are related to stress. Also, 40 Hz induced gamma enrichment within 15 min after light flickers and impaired the expression of long-term potentiation (LTP), while facilitated the expression of long-term depression (LTD) in the hippocampal CA1. Furthermore, 40 Hz light flicker enhanced the expression of corticosterone, rendered well-formed place cells unstable and improved animal’s learning and memory in novel local recognition test, which could be blocked by pre-treatment with the LTD specific blocker Glu2A-3Y. Conclusion: These finding suggested that 40 Hz chronic light flicker contains stress effects, promoting learning and memory in wild-type mice via LTD.

A neuronal code for space in hippocampal coactivity dynamics independent of place fields

Hippocampus CA1 place cells express a spatial neural code by discharging action potentials in cell-specific locations (′place fields′), but their discharge timing is also coordinated by multiple mechanisms, suggesting an alternative ′ensemble cofiring′ neural code, potentially distinct from place fields. We compare the importance of these distinct information representation schemes for encoding environments. Using miniature microscopes, we recorded the ensemble activity of mouse CA1 principal neurons expressing GCaMP6f across a multi-week experience of two distinct environments. We find that both place fields and ensemble coactivity relationships are similarly reliable within environments and distinctive between environments. Decoding the environment from cell-pair coactivity relationships is effective and improves after removing cell-specific place tuning. Ensemble decoding relies most crucially on anti-coactive cell pairs distributed across CA1 and is independent of place cell firing fields. We conclude that ensemble cofiring relationships constitute an advantageous neural code for environmental space, independent of place fields.

Choice of method of place cell classification determines the population of cells identified

Place cells, spatially responsive hippocampal cells, provide the neural substrate supporting navigation and spatial memory. Historically most studies of these neurons have used electrophysiological recordings from implanted electrodes but optical methods, measuring intracellular calcium, are becoming increasingly common. Several methods have been proposed as a means to identify place cells based on their calcium activity but there is no common standard and it is unclear how reliable different approaches are. Here we tested four methods that have previously been applied to two-photon hippocampal imaging or electrophysiological data, using both model datasets and real imaging data. These methods use different parameters to identify place cells, including the peak activity in the place field, compared to other locations (the Peak method); the stability of cells’ activity over repeated traversals of an environment (Stability method); a combination of these parameters with the size of the place field (Combination method); and the spatial information held by the cells (Information method). The methods performed differently from each other on both model and real data. In real datasets, vastly different numbers of place cells were identified using the four methods, with little overlap between the populations identified as place cells. Therefore, choice of place cell detection method dramatically affects the number and properties of identified cells. Ultimately, we recommend the Peak method be used in future studies to identify place cell populations, as this method is robust to moderate variations in place field within a session, and makes no inherent assumptions about the spatial information in place fields, unless there is an explicit theoretical reason for detecting cells with more narrowly defined properties.

Hippocampal place cells use vector computations to navigate

One function of the Hippocampal Cognitive Map is to provide information about salient locations in familiar environments such as those containing reward or danger, and to support navigation towards or away from those locations. Although much is known about how the hippocampus encodes location in world-centred coordinates, how it supports flexible navigation is less well understood. We recorded from CA1 place cells while rats navigated to a goal or freely foraged on the honeycomb maze. The maze tests the animal's ability to navigate using indirect as well as direct paths to the goal and allows the directionality of place cells to be assessed at each choice point during traversal to the goal. Place fields showed strong directional polarization in the navigation task, and to a lesser extent during random foraging. This polarization was characterized by vector fields which converged to sinks distributed throughout the environment. The distribution of these convergence sinks was centred near the goal location, and the population vector field converged on the goal, providing a strong navigational signal. Changing the goal location led to the movement of ConSinks and vector fields towards the new goal and within-days, the ConSink distance to the goal decreased with continued training. The honeycomb maze allows the independent assessment of spatial representation and spatial action in place cell activity and shows how the latter depends on the former. The results suggest a vector-based model of how the hippocampus supports flexible navigation, allowing animals to select optimal paths to destinations from any location in the environment.

State transitions in the statistically stable place cell population are determined by visual change

The hippocampus plays a central role in mammalian navigation and memory, yet an implementational understanding of the rules that govern the formation of individual place fields and the spatial-statistics of the population as a whole are lacking. We analysed large numbers of CA1 place fields recorded while rats foraged in different-sized environments up to 8.75 m2. We found that place cell propensities to form fields were proportional to open-field area, gamma-distributed, and conserved across environments. The properties of place fields varied positionally with a denser distribution of smaller fields near boundaries. Remarkably, the variation in field sizes and densities exactly countered each other, such that the population-level statistics were constant both within and between environments. Using a virtual reality replica of the environment, we showed that this variable rate of transition through the statistically stable place cell population was matched to change in the animals' visual scenes.

A computational grid-to-place-cell transformation model indicates a synaptic driver of place cell impairment in early-stage Alzheimer’s Disease

Alzheimer’s Disease (AD) is characterized by progressive neurodegeneration and cognitive impairment. Synaptic dysfunction is an established early symptom, which correlates strongly with cognitive decline, and is hypothesised to mediate the diverse neuronal network abnormalities observed in AD. However, how synaptic dysfunction contributes to network pathology and cognitive impairment in AD remains elusive. Here, we present a grid-cell-to-place-cell transformation model of long-term CA1 place cell dynamics to interrogate the effect of synaptic loss on network function and environmental representation. Synapse loss modelled after experimental observations in the APP/PS1 mouse model was found to induce firing rate alterations and place cell abnormalities that have previously been observed in AD mouse models, including enlarged place fields and lower across-session stability of place fields. Our results support the hypothesis that synaptic dysfunction underlies cognitive deficits, and demonstrate how impaired environmental representation may arise in the early stages of AD. We further propose that dysfunction of excitatory and inhibitory inputs to CA1 pyramidal cells may cause distinct impairments in place cell function, namely reduced stability and place map resolution.

Hippocampal place cell sequences differ during correct and error trials in a spatial memory task

Theta rhythms temporally coordinate sequences of hippocampal place cell ensembles during active behaviors, while sharp wave-ripples coordinate place cell sequences during rest. We investigated whether such coordination of hippocampal place cell sequences is disrupted during error trials in a delayed match-to-place task. As a reward location was learned across trials, place cell sequences developed that represented temporally compressed paths to the reward location during the approach to the reward location. Less compressed paths were represented on error trials as an incorrect stop location was approached. During rest periods of correct but not error trials, place cell sequences developed a bias to replay representations of paths ending at the correct reward location. These results support the hypothesis that coordination of place cell sequences by theta rhythms and sharp wave-ripples develops as a reward location is learned and may be important for the successful performance of a spatial memory task.

Place-cell capacity and volatility with grid-like inputs

What factors constrain the arrangement of the multiple fields of a place cell? By modeling place cells as perceptrons that act on multiscale periodic grid-cell inputs, we analytically enumerate a place cell's repertoire - how many field arrangements it can realize without external cues while its grid inputs are unique; and derive its capacity - the spatial range over which it can achieve any field arrangement. We show that the repertoire is very large and relatively noise-robust. However, the repertoire is a vanishing fraction of all arrangements, while capacity scales only as the sum of the grid periods so field arrangements are constrained over larger distances. Thus, grid-driven place field arrangements define a large response scaffold that is strongly constrained by its structured inputs. Finally, we show that altering grid-place weights to generate an arbitrary new place field strongly affects existing arrangements, which could explain the volatility of the place code.