The ability to learn and retrieve information is essential to the success of our efforts to effectively cope with daily life, and our individual collections of long-term declarative memories serve to guide us through time by forming the core of our personal identities. Further, as we age, long-term memory concerns are the most common cognitive complaint and are key concerns in neurological disorders. Understanding the neural mechanism that underlie declarative memory is thus a core problem in neuroscience. With support from the NSF Craig Stark and colleagues at Johns Hopkins University are making inroads into clarifying the way in which memories are stored and accessed in the human brain.
Structures in the medial temporal lobe (MTL) (including the hippocampus and the adjacent entorhinal, perirhinal, and parahippocampal cortices) are known to play a critical role in the ability to learn and remember facts and events. However it is not yet clear what the role is that each structure plays and how the structures interoperate to give us this remarkable ability to rapidly learn new information. In this project a total of ten experiments will be conducted that will further our understanding of this problem. The proposed experiments utilize a wide array of techniques in order to provide converging and complementary evidence: functional magnetic resonance imaging (fMRI) of brain activity in healthy volunteers, neuropsychological study of patients with damage to the hippocampus, and cognitive behavioral measures on healthy volunteers. In so doing, it will develop novel techniques for integrating these sources of information and it will explore new paradigms and new theoretical grounds.
The project is divided into three Aims. In the Aims 1 and 2, the neuroanatomical basis for pattern completion and pattern separation are examined. Pattern separation refers to the isolation of two or more similar patterns of activity (things to be remembered) into distinct, non-overlapping representations. Pattern separation is required whenever one needs to separate similar pieces of information that might otherwise interfere with each other (e.g., remembering that today, you parked your car in Lot B, although you usually park your car in Lot A). Pattern completion is pattern separation's complement. It refers to transforming an incomplete, distorted, or otherwise degraded pattern of activity into a complete pattern of activity based on your knowledge (e.g., while not having stored a perfect memory of where you parked today specifically, filling in the partial memory with details of Lot A...usually, but not always, correctly). Both are critical to successful memory, as we must both isolate similar memories when the differences are important and we must utilize the redundancy present in similar memories to overcome noise and capacity limitations when the differences do not matter. Computational models and evidence from animal studies have stressed these competing computational properties and have used neuroanatomical constraints to isolate a specific role for the hippocampus (or even a subregion of the hippocampus) in pattern separation. In the third Aim, the dynamics of single-item and associative memory encoding are explored using a backward-masking technique. This technique has revealed a novel dissociation in performance between single-item and associative memory. This project will determine whether the dissociation is dependent on the MTL by testing how the effect maps onto existing theories of memory such as the declarative / nondeclarative and remember / know dichotomies and how it is influenced by damage to the hippocampus and the rest of the MTL.
