Previous research has indicated a bias in memory-based decision-making, with people preferring options that they remember better. However, the cognitive mechanisms underlying this memory bias remain elusive. Here, we propose that choosing poorly remembered options is conceptually similar to choosing options with uncertain outcomes. We predicted that the memory bias would be reduced when options had negative subjective value, analogous to the reflection effect, according to which uncertainty aversion is stronger in gains than in losses. In two preregistered experiments ( = 36 each), participants made memory-based decisions between appetitive and aversive stimuli. People preferred better-remembered options in the gain domain, but this behavioral pattern reversed in the loss domain. This effect was not related to participants' ambiguity or risk attitudes, as measured in a separate task. Our results increase the understanding of memory-based decision-making and connect this emerging field to well-established research on decisions under uncertainty.
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http://dx.doi.org/10.1177/0956797620956315 | DOI Listing |
Nano Lett
January 2025
Corporate Research, TSMC, Hsinchu, 300-094, Taiwan.
Unprecedented penetration of artificial intelligence (AI) algorithms has brought about rapid innovations in electronic hardware, including new memory devices. Nonvolatile memory (NVM) devices offer one such attractive alternative with ∼2× density and data retention after powering off. Compute-in-memory (CIM) architectures further improve energy efficiency by fusing the computation operations with AI model storage.
View Article and Find Full Text PDFMethods Mol Biol
January 2025
Ecole Polytechnique Fédérale de Lausanne, School of Life Sciences, Institute of Bioengineering, Lausanne, Switzerland.
Gene expression memory-based lineage inference (GEMLI) is a computational tool allowing to predict cell lineages solely from single-cell RNA-sequencing (scRNA-seq) datasets and is publicly available as an R package on GitHub. GEMLI is based on the occurrence of gene expression memory, i.e.
View Article and Find Full Text PDFISA Trans
November 2024
The School of Electrical and Mechanical Engineering, University of Adelaide, Adelaide, SA, 5005, Australia. Electronic address:
This paper focuses on the design of event-triggered observer-based heterogeneous memory controllers for leader-following multi-agent systems with time-varying topology. In order to save limited on-board resources, a novel adaptive event-triggered strategy based on the nonlinear transformation law of the estimation error is proposed in this paper, which can effectively reduce some unnecessary data transmission due to small fluctuations after the estimation error converges. Then, a more general topology structure described by an interval type-2 fuzzy model is adopted, which contains both nonlinear time-varying law and uncertain parameters.
View Article and Find Full Text PDFNeural Netw
February 2025
Department of Engineering Management, University of Antwerp, Antwerp, Belgium. Electronic address:
Among various types of memory, working memory (WM) plays a crucial role in reasoning, decision-making, and behavior regulation. Neuromorphic computing is a well-established engineering approach that offers promising avenues for advancing our understanding of WM processes by mimicking the structure and operation of the human brain using electronic technology. In this work, a digital neuromorphic system is proposed and then implemented in hardware to illustrate the real-time WM process based on the spiking neuron-astrocyte network (SNAN).
View Article and Find Full Text PDFFront Epidemiol
November 2024
RAND Corporation, Boston, MA, United States.
Introduction: Seasonal influenza poses significant societal costs, including illness, mortality, and reduced work productivity. Vaccination remains the most effective strategy for preventing the disease, yet vaccination rates in the United States fall below 50% for adults. Understanding the factors influencing vaccination decisions is crucial for designing interventions to improve uptake.
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