There is growing evidence that false memories can occur in working memory (WM) tasks with only a few semantically related words and seconds between study and test. Abadie and Camos (2019) proposed a new model to explain the formation of false memories by describing the role of articulatory rehearsal and attentional refreshing, the two main mechanisms for actively maintaining information in WM. However, this model has only been tested in recognition tasks. In the present study, we report four experiments testing the model in recall tasks in which the active maintenance of information in WM plays a more important role for retrieval. Short lists of semantically related items were held for a short retention interval filled with a concurrent task that either impaired or not the use of each of the WM maintenance mechanisms. Participants were asked to recall the items immediately after the concurrent task (immediate test) or later, at the end of a block of several trials (delayed test). In the immediate test, semantic errors were more frequent when WM maintenance was impaired. Specifically, rehearsal prevented the occurrence of semantic errors in the immediate test, while refreshing had no effect on their occurrence in this test, but increased semantic errors produced only in the delayed test. These results support Abadie and Camos (2019) model and go further by demonstrating the role of active information maintenance in WM in the emergence of false memories. The implications of these findings for understanding WM-LTM relationships are discussed.
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http://dx.doi.org/10.1016/j.cognition.2024.105901 | DOI Listing |
Sci Rep
January 2025
Department of Electrical and Electronics Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India.
The increasing prevalence of network connections is driving a continuous surge in the requirement for network security and safeguarding against cyberattacks. This has triggered the need to develop and implement intrusion detection systems (IDS), one of the key components of network perimeter aimed at thwarting and alleviating the issues presented by network invaders. Over time, intrusion detection systems have been instrumental in identifying network breaches and deviations.
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December 2024
The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
Background: Amyloid beta (Aβ) deposition marks an early stage in the progression of Alzheimer's disease (AD), detectable in‐vivo years before symptoms emerge and targeted by recently FDA‐approved drugs. This has propelled advancements in understanding, measuring, and treating AD, paving the way for disease prevention in those at risk. However, the psychological impact of disclosing Aβ status to cognitively unimpaired individuals remains underexplored.
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December 2024
Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
Background: Reduced complexity of resting‐state fMRI has been associated with mild cognitive impairment (MCI) and Alzheimer's diseases (AD) in cross‐sectional cohorts. However, the trajectory of complexity in AD progression remains unknown. We conducted complexity analyses in a longitudinal AD dataset.
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December 2024
Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
Background: The existing literature has established that Alzheimer's disease (AD) is typically characterized by changes in memory‐associated temporal and parietal lobe atrophy and hypometabolism. However, some individuals clinically diagnosed with AD do not have biomarkers consistent with AD pathology. In this cross‐sectional study, we aimed to investigate differences in memory consolidation, temporal and parietal lobe atrophy, as well as temporal and parietal lobe metabolism within a clinically diagnosed cohort of individuals with amnestic Mild Cognitive Impairment (aMCI) who were either positive or negative for amyloid.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, USA
Background: Highly specific ATN plasma biomarker assays for neurodegenerative diseases have been developed, but their associations with cognition vary in different populations. Kidney disease, common in diabetes, may decrease the predictive precision of those biomarkers. The aim of this study was to characterize for the first time the relationships between plasma ATN biomarkers and cognitive function in adults with T1D.
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