# Linking Hippocampal Replay Content to Learning and Decision-Making > **NIH NIH F32** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2021 · $71,390 ## Abstract PROJECT SUMMARY / ABSTRACT Memory is an integral component of human cognition, and when memory processes go awry, the result is devastating neurological disorders of memory loss including Alzheimer's disease and other forms of dementia. One essential role of normal memory processes is to use previous experience to guide decisions about future actions. Thus, research to define the neural mechanisms of memory processes is important to understand both normal brain function and what goes wrong in memory loss disorders. Further, insights from these studies could help develop new treatments for these disorders. Recent work showed that synchronized neuron firing events in the hippocampus called sharp wave ripples (SWRs) that occur during awake immobility are required for rapid learning during spatial memory tasks. SWRs often contain specific place-cell firing sequences that closely resemble firing during prior experiences (“replay” events), suggesting a potential neural mechanism for retrieval of specific prior experiences. However, not all awake SWRs contain replay events that encode experiences related to the current environment, and so whether the specific content of replay is required for learning remains an unanswered question. I hypothesize that content-specific replay events serve to retrieve specific prior experiences and so are required for learning and decision-making. To date, this hypothesis has not been directly tested and the lack of tests is a major gap in our understanding of neural mechanisms of memory processes. In preliminary work, I have developed a system that decodes and classifies replay events in real-time and can provide behavioral or neural feedback based on the content of a replay event. I will use this system to test three related hypotheses, (1) replay content can be modulated by behavioral conditioning, (2) specific replay content can drive behavior, and (3) specific replay content is required for learning. In addition to these experiments, my fellowship training plan includes research and academic goals. My research goals are to investigate fundamental neural mechanisms of memory processes and to learn the methods of in vivo physiology and computational neuroscience. My academic goals are to build a strong foundation in computational neuroscience and continue to improve the career development skills I will need for my transition to independence at the end of this fellowship. Together, the labs of my sponsor, Loren Frank, and co-sponsor, Uri Eden, and the UCSF scientific community will provide an excellent training environment. Dr. Frank is a leading expert in the field of chronic hippocampal recording and neural data analysis methods. Dr. Eden is an expert in methods of computational and theoretical neuroscience, including the algorithms I will use in my experiments. UCSF is a premier academic research institution for medicine and neurobiology with a strong focus on collaboration and plentiful career development resources ... ## Key facts - **NIH application ID:** 10173642 - **Project number:** 5F32MH123003-02 - **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO - **Principal Investigator:** Michael Edward Coulter - **Activity code:** F32 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $71,390 - **Award type:** 5 - **Project period:** 2020-06-01 → 2023-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10173642 ## Citation > US National Institutes of Health, RePORTER application 10173642, Linking Hippocampal Replay Content to Learning and Decision-Making (5F32MH123003-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10173642. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*