Work

A dynamic model of context-based retrieval

Year: 2025

Type: article

Abstract: We propose a comprehensive model of how experiences are encoded and retrieved from memory. At the core of the model is a dynamic retrieval process incorporating two essential mechanisms: iterative retrieval, whereby information is sequentially sampled from memory to access the full history of experiences; and competitive retrieval, whereby the most prominent features in memory inhibit the recollection of other features. Together with context-based encoding, the model quantitatively explains well-known facts about response order and inter-response times in recall experiments. We show that our retrieval process maps closely to existing decision frameworks, such as drift–diffusion models, suggesting that the memory system plays a fundamental role in a wide-ranging set of decision-making settings.

Source: Journal of Mathematical Psychology

DOI: 10.1016/j.jmp.2025.102957

Authors: Madison D. Paron, James D. Paron, Michael J. Kahana

Institutions: Stanford University, University of Pennsylvania

Language: English

Topic: Memory Processes and Influences

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $3,440

Funder: University of Pennsylvania