# Computational and Circuit Mechanisms Underlying Rapid Learning > **NIH NIH U19** · UNIVERSITY OF WASHINGTON · 2022 · $2,410,520 ## Abstract PROJECT SUMMARY/ABSTRACT The mammalian brain has a remarkable ability to store and retrieve information. Detailed memories can be formed after as little as one exposure, and those memories can be retained for decades. This ability is compromised following damage to structures located in the medial temporal lobe, including the hippocampus and the adjacent cortex. Over the past decade, many studies have highlighted interactions between the hippocampus and neocortex, in particular, the prefrontal cortex (PFC) and posterior parietal cortex (PPC), as having an essential role in memory consolidation. However, the circuit mechanisms that support memory consolidation are not well-understood, particularly in the primate brain. Impaired memory is an important component of diseases such as Alzheimer's disease, temporal lobe epilepsy, depression, and schizophrenia that collectively affect over twenty million Americans. Our long-range goal is to contribute to a better understanding of the neural mechanisms that underlie memory processes, in order to bring us closer to developing new therapies for these disabled patients. Psychological theories and behavioral studies have suggested that rapid, single-trial accumulation of information is facilitated by prior knowledge, a cognitive map or “mental schema” that provides a framework onto which new information can be assimilated. This concept is relevant for understanding potential hippocampal-neocortical interactions in the service of memory consolidation. The experiments proposed here will directly examine the neural circuits in the hippocampus, PFC, and PPC that support schema development and new learning. The overall goal of this U-19 Program is to develop a comprehensive theory of the circuit mechanisms that support rapid learning. To achieve these goals, we will make use of a multi-laboratory research framework with an ambitious effort that requires multiple areas of expertise, exemplified by our team members. Our team effort is organized around four Research Projects, each supported by Data Science and Administrative Cores. Through parallel projects in monkeys and humans, we will perform large-scale recordings simultaneously across the hippocampus, PFC and PPC to assess modulations in cross-regional connectivity during schema development and new association and categorization learning. Complementary theoretical approaches will integrate large-scale circuit modeling of the human and nonhuman primate brain based on measured mesoscopic connectivity and training recurrent neural networks to perform cognitive tasks. We will test the hypothesis that in the course of schema instantiation, a task structure is encoded in the form of a low-dimensional structure in the space of connection weights, which is reflected in a low- dimensional subspace of neural dynamics. During new learning, the system benefits from the schema to narrow weight parameter search, thereby speeding up learning. We hypothesize that this process ... ## Key facts - **NIH application ID:** 10456064 - **Project number:** 5U19NS107609-05 - **Recipient organization:** UNIVERSITY OF WASHINGTON - **Principal Investigator:** Elizabeth A Buffalo - **Activity code:** U19 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $2,410,520 - **Award type:** 5 - **Project period:** 2018-09-15 → 2024-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10456064 ## Citation > US National Institutes of Health, RePORTER application 10456064, Computational and Circuit Mechanisms Underlying Rapid Learning (5U19NS107609-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10456064. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*