Hippocampal spatial memory representations in mice are heterogeneously stable

Abstract

The population of hippocampal neurons actively coding space continually changes across days as mice repeatedly perform tasks. Many hippocampal place cells become inactive while other previously silent neurons become active, challenging the belief that stable behaviors and memory representations are supported by stable patterns of neural activity. Active cell replacement may disambiguate unique episodes that contain overlapping memory cues, and could contribute to reorganization of memory representations. How active cell replacement affects the evolution of representations of different behaviors within a single task is unknown. We trained mice to perform a Delayed Non-Match to Place (DNMP) task over multiple weeks, and performed calcium imaging in area CA1 of the dorsal hippocampus using head-mounted miniature microscopes. Cells active on the central stem of the maze “split” their calcium activity according to the animal’s upcoming turn direction (left or right), the current task phase (study or test), or both task dimensions, even while spatial cues remained unchanged. We found that different splitter neuron populations were replaced at unequal rates, resulting in an increasing number of cells modulated by turn direction and a decreasing number of cells with combined modulation by both turn direction and task phase. Despite continual reorganization, the ensemble code stably segregated these task dimensions. These results show that hippocampal memories can heterogeneously reorganize even while behavior is unchanging.Significance statementSingle photon calcium imaging using head-mounted miniature microscopes in freely moving animals, has enabled researchers to measure the long term stability of hippocampal pyramidal cells during repeated behaviors. Previous studies have demonstrated instability of neural circuit components including dendritic spines and axonal boutons. It is now known that single units in the neuronal population exhibiting behaviorally relevant activity eventually become inactive and that previously silent neurons can quickly acquire task-relevant activity. The function of such population dynamics is unknown. We show here that population dynamics differ for cells coding distinct task dimensions, suggesting such dynamics are part of a mechanism for latent memory reorganization. These results add to a growing body of work showing that maintenance of episodic memory is an ongoing and dynamic process.

Stable task information from an unstable neural population

“…In our recent work ( Driscoll et al, 2017 ), we found that neural activity–behavior relationships in individual posterior parietal cortex (PPC) neurons continually changed over many days during a repeated virtual navigation task. Similar ‘representational drift’ has been shown in other neocortical areas and hippocampus ( Attardo et al, 2015 ; Ziv et al, 2013 ; Levy et al, 2019 ). Importantly, these studies showed that representational drift is observed in brain areas essential for performing the task long after the task has been learned.…”

Consistent population activity on the scale of minutes in the mouse hippocampus

“…To distinguish consistent sequences from stochastic dynamics (Figure 1), we examined the consistency of the neuronal dynamics across two timescales while mice performed reward-based navigational tasks (Mau et al, 2018;Levy, Kinsky, Mau, Sullivan, & Hasselmo, 2019;Rubin et al, 2015). In all experiments, each session consists of multiple trials, during which mice were trained to navigate through an environment to obtain rewards (Figure 2).…”

Fragmented Spatial Maps from Surprisal: State Abstraction and Efficient Planning

“…First, it suggests that variations in the firing of grid and place cells on di↵erent visits to a location might be due not only to variable paths taken within a single map [75] but to the retrieval of entirely di↵erent maps. Second, these multiple, stochastically generated maps might subsequently be easy to harness for contextual di↵erentiation, for instance like "splitter" cells [58,[76][77][78].…”