Memories are crucial to our lives. With them, we generate a unique history, connect with the world around us, and make informed decisions. Memory loss occurs as we get older, and more pervasive changes in memory function can be among the earliest signs of Alzheimer?s disease, a major public health challenge affecting more than 5.6 million Americans. Past studies have shown that the ability to discriminate among similar mnemonic experiences (i.e. pattern separation) is an early sign of memory impairment in older adults at risk for Alzheimer?s disease. This disruption in memory is thought to be an early harbinger of subsequent cognitive decline and may be a suitable therapeutic target in the earliest stages of the disease. However, such targeting is impossible without a complete understanding of the circuit-level dynamics that support pattern separation in humans. While computational theories have long suggested a necessary role for interactions between the hippocampus and the neocortex, the field has struggled with challenges in identifying such network level dynamics in humans due to limited temporal resolution using fMRI and limited spatial resolution using EEG. I propose to fill this gap in knowledge using a rare and unique opportunity to record from both the neocortex and the hippocampus with superior spatial and temporal resolution in humans implanted with intracranial electrodes for clinical monitoring while they engage in a pattern separation memory task. I will collect neural recording data from a minimum of 15 patients undergoing clinical monitoring with surgically implanted depth electrodes in the hippocampus and the neocortex at the UCI Comprehensive Epilepsy Unit. I propose three specific aims: (1) Test the hypothesis that increased theta power in the hippocampus and neocortex will predict successful discrimination performance on pattern separation task; (2) Test the hypothesis that during encoding, hippocampal-neocortical interactions will be directionally biased such that the hippocampus leads the cortex, reflecting the integration of newly learned information into neocortical sites; and (3) Test the hypothesis that during retrieval, hippocampal-neocortical interactions will be directionally biased such that the cortex leads the hippocampus, reflecting the access of memory content from neocortical sites. The proposed studies are feasible with the excellent research and training environment at UC Irvine and the availability of clinical infrastructure and an epilepsy monitoring unit with research-dedicated recording equipment. Using these resources, I have already collected preliminary data in support of all three hypotheses. With the joint mentorship of Dr. Michael Yassa and Dr. Jack Lin, I will receive advanced training in clinical and cognitive neuroscience. With additional mentorship of Dr. Lee Swindlehurst in electrical engineering, I am employing techniques to analyze high dimensional data and directionality measures for network analysis. With the help of this constellation of mentors, I aim to fill a critical gap in knowledge about memory mechanisms in the human brain, with the overarching goal of applying this knowledge to reversing memory loss in aging and Alzheimer?s disease.
Alzheimer?s disease is a devastating illness affecting more than 5.8 million Americans, and with the world?s population rapidly aging, the public health and economic impact of Alzheimer?s disease is enormous. Memory impairment is the first sign of cognitive change in Alzheimer?s disease, but we still do not have a good understanding of the mechanisms by which these memory processes may be impacted. This proposal sets the stage for an improved understanding of memory mechanisms by using depth electrode recordings in humans to track how memories are formed and retrieved with superior spatial and temporal resolution.
