Project Summary / Abstract The hallmark feature of episodic memory is the ability to link events with their temporal and situational contexts. This ability allows for memories to be truly autobiographical. Importantly, models suggest that the fate of our memories is strongly influenced by latent reminders, reactivations, and retrievals – processes normally invisible to the experimenter. The proposed research aims to illuminate the neural and cognitive mechanisms underlying human episodic (contextually-mediated) memory through both computational modeling and the analysis of intracranial and scalp electroencephalographic (EEG) recordings taken as neurosurgical patients and healthy adults undergo virtual reality experiences and then search their memory for material studied therein. We will use a model-based approach coupled with multivariate pattern analysis applied to electrophysiological data. Our first aim is to elucidate how memory reactivation, driven by repetition of items or their contexts, shapes subsequent recall and memory organization. We further seek to decode endogenous memory reactivation events (rehearsal and replay) from neural data, and to determine their influence on subsequent recall behavior (Aim 2). Finally, we will connect memory retrieval and decision-making processes by investigating how behavioral and neural retrieval dynamics shape value-based decision making. This work will serve as an important bridge between the behavioral and neurobiological approaches to human memory.