# Stability and Robustness of Hippocampal Representations of Space

> **NIH NIH R01** · CALIFORNIA INSTITUTE OF TECHNOLOGY · 2022 · $1,028,181

## Abstract

PROJECT SUMMARY
How does the brain balance the need to preserve prior knowledge with the necessity to continuously learn
new information? The tradeoff between stability and plasticity is inherent in both biological and artificial
learning systems constrained by finite resources and capacity. The hippocampus is a brain region critical for
memory formation and spatial learning, which can provide a powerful experimental system for characterizing
this tradeoff. The role of the hippocampus in spatial cognition is supported by the finding that pyramidal
neurons in this area (place cells) fire in specific locations in an environment (place fields). The population of
place cells active in an environment is believed to form a neural representation or cognitive map of that
environment. Spatial learning is critical for survival and involves two competing constraints: representations of
space must be plastic to enable fast learning of new environments and changes in behavioral contingencies,
and stable over time to enable recognition of familiar environments, reliable navigation, and leveraging of
previous learning. How do these competing constraints affect the stability of place fields across time? The
experimental characterization of the long-term stability of spatial representations in the hippocampus has
been challenging as it requires tracking the activity of multiple place cells across extended periods of time
(days to weeks). We propose to use novel approaches in large-scale electrophysiology and imaging in
behaving rodents to characterize which neurons change their spatial tuning and how these changes depend
on behavior. Furthermore, we will use recordings and circuit perturbations to characterize the activity patterns
that predict changes in tuning stability. Our analysis will be carried out in the context of a theoretical
framework for understanding the interplay between plasticity and stability of hippocampal representations.
Characterizing the evolution of neural representations is of fundamental importance in understanding how
information is maintained across brain circuits and how such maintenance is perturbed in brain disorders.

## Key facts

- **NIH application ID:** 10463556
- **Project number:** 5R01NS121918-02
- **Recipient organization:** CALIFORNIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** JOHN C DOYLE
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,028,181
- **Award type:** 5
- **Project period:** 2021-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10463556

## Citation

> US National Institutes of Health, RePORTER application 10463556, Stability and Robustness of Hippocampal Representations of Space (5R01NS121918-02). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10463556. Licensed CC0.

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