A Computational Framework for Assessing the Integration of Category Knowledge in Episodic Memory in Early Childhood

This award was provided as part of NSF's Social, Behavioral and Economic Sciences Postdoctoral Research Fellowships (SPRF) program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Elizabeth Bonawitz at Rutgers University - Newark, this postdoctoral fellowship award supports an early career scientist investigating the role of prior category knowledge, a mechanism that can reduce uncertainty in recalled information, in the encoding, storage, and retrieval of information from developing (i.e. children) episodic memory systems. Converging evidence suggests that individuals with well-developed memory systems (i.e. young adults) possess prior category knowledge and expectations that are well-calibrated to the statistical regularities of the environment and that they use this information optimally to reduce uncertainty and to fill-in noisy and incomplete episodic representations when reconstructing events from memory. However, in early memory development, category knowledge and expectations might not be as well established, and episodic representations might be severely impoverished. Thus, understanding if and how children integrate these noisy, less defined pieces of information to reconstruct events from memory is critical. To this end, the current project amalgamates computational approaches with experimental methods to elucidate the role of category knowledge in event memory reconstruction in early development. The empirical goal of this project is to investigate the interplay between category information and noisy episodic memories in early childhood, providing a unique opportunity to assess the goals and behavior of the developing memory system when semantic knowledge and episodic traces are lacking. The computational goal of this research program is to evaluate whether the integrative process is employed to reduce uncertainty in reconstructed events early in memory development and understand the tradeoffs of using category knowledge and episodic memories, given the noise in both.

In a series of experiments, this project will first, empirically quantify the prior category knowledge that younger and older children bring to the task of remembering, and evaluate episodic memory to elucidate the role of prior knowledge. After this project will employ probabilistic modeling to assess the weighting of category and episodic information in reconstructed events, and to compare this integrative model against several alternatives. It will also evaluate individual and group differences to reveal potential developmental shifts in the integration of category and episodic information in recall. Taken together, this project will 1) increase our understanding of the cognitive mechanisms early learners use (e.g. category knowledge) to cope with noisy and incomplete episodic representations when trying to recall events from memory, 2) shed light on how the use of this mechanism changes across memory development, and 3) proffer a comprehensive computational framework to flexibly characterize episodic memory from early childhood into adulthood. The development of such a computational paradigm will enhance theories and methodologies for assessing episodic memory in children. Exploring this critical period of memory development can reveal whether developmental changes in episodic memory performance are marked by the ability to efficiently integrate category knowledge and noisy episodic representations. Importantly, understanding the goals and development of episodic memory creates an opportunity to exploit its natural operation and constraints to inform interventions for improving memory performance across the lifespan.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.