A Retrieved Context Model of Serial Recall and Free Recall
Year: 2024
Type: article
Abstract: A full characterization of memory must include how participants use exogenous and endogenous cues to guide retrieval. In free recall, in which endogenous cues play a large role, retrieved context theories have emerged as a leading explanation of data on the dynamics of memory search (Lohnas & Healey, 2021). More recently, Logan and colleagues have advanced a retrieved context model to explain data on serial recall and motor production (Logan, 2021; Logan & Cox, 2021; Logan, 2018; Logan & Cox, 2023). Comparisons of recall transitions have further highlighted similarities among these tasks (e.g., Bhatarah et al., 2008; Golomb et al., 2008). Here I evaluate retrieved context theory’s ability to simultaneously account for data from these classic recall procedures. I show how a serial version of the context maintenance and retrieval model (termed sCMR) can account for dissociations between serial position curves and temporal clustering effects. I also show how sCMR can account for grouping effects in serial recall, extending the assumptions of grouping from free recall (Lohnas et al., 2023). The sCMR model provides a common theoretical framework to harmonize the disparate phenomena studied using these classic memory procedures, but also reveals the distinctions between serial and free recall through their relative dependence on different model-based mechanisms.
Source: Computational Brain & Behavior
Author: Lynn J. Lohnas
Institution: Syracuse University
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $3,090
Funder: University of Pennsylvania
OpenAlex ID: W4404165649