About his PhD project

The hippocampal brain region is essential for episodic memory, which relies on the coordinated discharge of cell assemblies within transient events known as Sharp Wave Ripples (SPW-Rs). The electrophysiological signature of SPW-Rs is considered evidence for the involvement of specific neural subcircuits in memory formation. Our work focuses on exploring the functional diversity of these events and their role in memory processing. Recent findings suggest that, contrary to traditional views, SPW-Rs are not uniform but exhibit distinct profiles, likely involving different neural circuits and functions. The project aims to develop a novel classification system for these events using advanced machine learning techniques such as Variational Autoencoders and dimensionality reduction methods like UMAP, based on electrophysiological recordings from the hippocampus in adult mice. Additionally, we will construct computational models of hippocampal networks to investigate how connectivity patterns influence ripple characteristics. The overarching goal is to determine how the heterogeneity of SPW-Rs relates to their functional role in organizing and consolidating episodic memories, thereby providing new insights into hippocampal neural dynamics.