Sean M. Polyn, PhD - US grants

[unreadable] DESCRIPTION (provided by applicant): Evidence from neuroimaging and lesion studies indicates that both medial temporal lobe (MTL) and prefrontal cortex (PFC) contribute to episodic memory performance. We present a computational neural network model of how interactions between MTL and PFC support performance on free recall tests. The MTL component has already been used to account for a wide range of recognition memory findings (Norman & O'Reilly, in press). The PFC component is based on recently developed models of how PFC supports cognitive control. These models (e.g., Frank, Loughry & O'Reilly, 2001) posit that PFC actively maintains aspects of presented stimuli via multiple parallel 'stripes' that be updated separately. On each trial, information in PFC can be maintained, or can be replaced by aspects of the current stimulus. Over time, the pattern of activity in PFC can be viewed as an evolving 'context vector'. At study, the current state of this PFC context vector is associated with item representations via the hippocampus, and at test PFC can cue memory for studied items. At a high level, this approach has much in common with more abstract models of temporal context memory (e.g. Howard & Kahana, 2002a). We use the computational model to generate specific testable predictions about the performance of normal and frontally damaged subjects in a variety of free recall paradigms. Modifications to the model are proposed that will allow us to capture a wider range of behavioral data, including primacy and subjective organization. This framework allows us to develop a mechanistic understanding of prefrontal contributions to episodic memory. [unreadable] [unreadable]

Despite their importance, the neural and cognitive mechanisms underlying memory search and recall are poorly understood. With funding from the National Science Foundation, cognitive neuroscientist Dr. Sean Polyn of Vanderbilt University, is developing a computational model of the human memory system. His goal is to understand how the brain supports memory formation and memory search. The human brain contains sophisticated neural circuitry that allows humans to form detailed memories of past experience and to carry out flexible, goal-directed searches through those memories. Major issues being addressed in this project include determining how and why distraction impairs the ability to remember recent events, and determining how memory can be searched for a particular class of items as opposed to another (for example, if one is trying to remember which vegetables one needs to buy at the supermarket, it doesn't help to recall the baked goods one needs).Dr. Polyn's computational model, the Context Maintenance and Retrieval model, suggests that studying for a later memory test (for example, a student studying vocabulary for the SAT) results in associations between neural representations of the to-be-remembered material and a retrieval cue that is used in later reactivating the memory representations of the studied material. In experiments, participants study a series of items presented one at a time, and at the end of the series they are asked to remember in order as many of the studied items as they can. During the task, investigators record brain activity using electroencephalography, which records fluctuations in voltage at the scalp that are generated by the brain. This brain activity is used computationally to predict whether a particular piece of information will be remembered and also to predict the order in which the memories will be retrieved.

The ability to engage in self-initiated memory search is critical to a healthy, independent life. Performance on recall-based memory search tasks is a sensitive predictor of cognitive decline and is one of the tests used to diagnose Alzheimer's disease, schizophrenia, and other neurocognitive disorders. This project is providing insights into the mechanisms of memory deficits that might be related to deficits seen in the many brain disorders affecting memory. The project will potentially lead to new treatments, once the roles of these brain regions are better understood.