Implicit boundaries are remembered better than non-boundaries in statistical learning

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Publication Details

Journal
Memory
Published
2026-09-04
DOI
https://doi.org/10.1080/09658211.2026.2719605
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
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article

Implicit boundaries are remembered better than non-boundaries in statistical learning

Jeffrey J. Starns, Andrew L. Cohen, Tejas Savalia
Memory
Neural Networks and Applications
article

Implicit boundaries are remembered better than non-boundaries in statistical learning

Jeffrey J. Starns, Andrew L. Cohen, Tejas Savalia
article en

Abstract

Changes in temporal context have been shown to impact episodic memory of the "boundary" items involved in creating this temporal context. However, in most prior studies, changes in temporal context have been operationalised explicitly, typically through perceptually obvious visual or auditory stimuli that form a boundary between the previous and current context. In this work, we explore how recognition of items is impacted when temporal context change is operationalised implicitly through the order of presentation during the study phase. 59 participants were exposed to a rotation judgment cover task for 15 randomly generated polygon items. Around half of the participants were presented with these items in a random order. The other half were presented with items such that 6 items formed "boundaries" that led in and out of 3 temporal clusters. Similar to findings where boundaries are explicitly operationalised, we show that implicit boundaries are also better remembered than non-boundary items.

Memory
University of Massachusetts Amherst (US), University of Bouira (DZ)
Openalex Percentile: Top 99%
Neural Networks and Applications
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Implicit boundaries are remembered better than non-boundaries in statistical learning — Jeffrey J. Starns, Andrew L. Cohen, et al. · Memory (2026) | TGRS Research Map | TGRS