Using Anatomy and Computational Theory to Inspire Neurophysiological Experiments on Information Processing Through the Hippocampus.

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This article is a personal history of the background, ideas, and motivations behind the major discoveries from my lab in the past 27 years. Tracing the main themes back to my training as a graduate student and a postdoc, I discuss how all of our work has been influenced by a desire to use anatomical and computational literature to inspire and constrain the experimental questions we have addressed. The backstory of two fundamental discoveries made in the early days on my independent research program are described: (a) differences between DG, CA3, and CA1 population dynamics in relation to computational theories of pattern separation and pattern completion and (b) differences in the types of information conveyed to the hippocampus from its lateral and medial entorhinal cortex inputs. Also described are how these initial findings set the foundation for numerous subsequent discoveries as we followed the data from one experiment to the next, with the goals of understanding how information is represented and transformed through the hippocampal formation in support of spatial learning and episodic memory.