Daoyun Ji, Baylor College of Medicine and Steve Cox Rice University,
We are interested in the neural mechanisms of episodic memory, the kind of memory for everyday events and experiences that largely define who we are. Events and experiences are encoded by specific neural activity patterns. The Cox lab asks; how are these patterns stable represented by Hebbian Cell Assemblies and how stable are these patterns to perturbations in environmental cues? It is hypothesized that the same patterns are reactivated afterwards during memory retrieval and consolidation. The Ji lab asks; when reactivations occur, what is there exact nature, and how they are related to memory processing?
We train both real and imaginary rats to run mazes as a model to study episodic-like experience. At the same time, we record/model a large number of neurons in the rat's hippocampus to examine how neuronal patterns are encoding during the running experience and are later reactivated. The central pattern of interest is the place field, a fixed region in space in which a specific cell fires and outside of which it is quiet. The student will mainly analyze the recorded data and re-construct the activated and reactivated memory patterns with the option to conduct actual recording and/or large scale parallel simulations. We will focus on how hippocampal neurons encode novel/familiar behavioral experiences and how these are re-activated by sensory cues and during offline periods, such as sleep. The first task will be to implement and test the Adaptive Filtering Approach of Frank et al to the quantification and evolution of place fields.