Hippocampal representational drift and the impact of Alzheimer’s disease

The hippocampus (HC) plays a pivotal role in spatial navigation and memory in the human brain. Place cells, specialised neurons residing within the hippocampus, exhibit selective firing patterns corresponding to specific spatial locations, collectively contributing to the cognitive mapping of the environment. In healthy state, the place fields in the CA1 region exhibits continuous representational turnover [1].

Spatial navigation is disrupted in Alzheimer’s Disease (AD). AD, a neurodegenerative disorder characterised by progressive cognitive decline, is associated with deficits in learning and memory. Its hallmark features include the accumulation of protein aggregates, such as amyloid beta (Aβ) plaques and tau tangles, in the brain. These pathological changes lead to abnormal neural network excitability in the hippocampus. In the early stages of AD, the neural circuits exhibit hyperexcitability, which shifts to hypoexcitability as the diseases progresses.

Our study aims to understand the baselines CA1 place cell dynamics and the impact of AD on them. We used two-photon calcium imaging data of healthy and diseased mice running in a virtual environment to monitor place cell activity. We have found that in healthy mice, CA1 place fields retain some degree of stability despite their dynamic representations. We also observed that the place field movements follow a characteristic distribution, marked by local fluctuations and random relocations. Moreover, we showed that there was an overrepresentation of place cells for salient locations, and they exhibited higher place field stability [2]. Next, we intend to analyse how the aberrant circuit dynamics in AD affect these dynamics.

Understanding the dynamics between the healthy and diseased states may provide insights into the underlying mechanisms of spatial memory deficits in AD. By analysing the representational dynamics in conditions of hyper-excitability and hypo-excitability, we also intend to uncover the mechanisms driving representational drift.