Neural mechanism of spatial navigation and memory

National Institute Of Neurological Disorders And Stroke

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Abstract

Our current research projects are centered around two aims: Aim 1. Investigating the neural mechanism underlying spatial representation in the medial entorhinal cortex (MEC). We harness the cellular-resolution optical tools to test the hypotheses of many theoretical models at the microcircuit level, which was previously inaccessible using conventional approaches. Aim 2. Uncovering the circuit and molecular mechanisms of the MEC in the formation, maintenance, and retrieval of spatial memory. We particularly study the activity, structural, and molecular dynamics of the MEC during these processes and investigate the causal link between the MEC dynamics and spatial memory. In the past fiscal year, we made significant progress under the two aims. Under aim 1, we investigated we investigated how MEC neural dynamics encodes identity of visual landmarks during navigation. Our study primarily focused on cue cells, which responded to individual landmarks during virtual navigation. Cue cells represented landmark identity by exhibiting more distinct activity patterns between visually disparate landmarks than identical ones. The representation was modulated by the spatial shift of cue cell activity relative to landmark location. Moreover, the identity encoding by the same cue cell population changed between different environments but was maintained within the same environment despite increased experience. In contrast, landmark location encoding by cue cells was regulated by experience, suggesting different mechanisms underlying the encodings of landmark identity and location. Finally, compared to cue cells, grid cells weakly encoded landmark identity but more robustly encoded landmark location. Thus, the MEC integrates both spatial and nonspatial information during navigation, but potentially through different circuit mechanisms. This study is currently under revision. Additionally, we have also been studying activity relationships of different cell types in the MEC during navigation. Under aim 2, we collaborated with Dr. Ila Fiete’s laboratory at MIT and Dr. Veronica Alvarez’s laboratory at NIMH in investigating how synaptic plasticity shapes grid cell activity during spatial learning. We longitudinally record grid cells with two-photon calcium imaging over 10 days as mice learn operant tasks in novel virtual linear tracks. We observe that spatial tuning of grid cells is present immediately in novel tracks but evolves as a significant fraction of spatial fields shift backward on a run-by-run basis, within and across days. Backward shifts are more prevalent and persistent in successful learners. The fields gradually stabilize across days, anchored by landmarks, suggesting a slow plasticity mechanism that results in an increasingly fragmented and stable map. The backward shifts partially reset daily, reflecting a slower consolidation timescale. We show that though individual fields of a cell shift differentially, co-active fields of co-modular grid cells shift together, indicating their coupled dynamics keep them on the same two-dimensional torus during this plastic period. Next, we build a simple entorhinal-hippocampal model (with Fiete’s lab) that explains the diverse phenomena - grid field shifts, fragmentation, and increasing fidelity of the spatial map - and predicts slow Hebbian plasticity in the return hippocampal-to-entorhinal pathway. Finally, using ex vivo slice electrophysiology (with Alvarez’s lab), we show that plasticity in an indirect hippocampus-to-MEC pathway correlates with spatial learning performance and could account for the hypothesized slow plasticity of the model. Together, our study provides multifaceted evidence of slow plasticity in synapses from the hippocampus to the MEC, elucidating the formation of stable and fragmented maps that combine internal and cue-driven positional estimates in rich environments, elucidating cognitive map formation during spatial learning. Furthermore, we are also wrapping up a studying on the neural dynamics of the MEC underlying spatial learning deficits in a tauopathy mouse model.