It is widely believed that semantic activation from print is automatic in the sense that it is capacity free. Two experiments addressed this issue in the context of the Psychological Refractory Period (PRP) paradigm. Participants identified whether a tone was high or low in pitch in Task 1, and named the color carried by an irrelevant word in Task 2. Tasks 1 and 2 were separated by a short or long SOA. In Experiment 1 incongruent color words and neutral words served as irrelevant distractors, whereas in Experiment 2 the distractors consisted of incongruent color associates (e.g., tomato) and the same set of neutral items. Additionally, the proportion of short and long SOAs between Task 1 and Task 2 varied across blocks, within subjects (e.g., 80:20), so as to determine whether the bottlenecking of semantic activation and response competition reported previously is best construed as structural, or subject to performance optimization. Replicating Miller, Ulrich, and Rolke (2009), SOA Proportion interacted with SOA in both experiments, consistent with performance optimization. In contrast, replicating Besner and Reynolds (2014), SOA and Congruency had additive effects on RT in both experiments, consistent with an account in which both response competition and semantic activation are bottlenecked. The best account to date is that (i) semantic processing and response competition are structurally bottlenecked (require some form of capacity), whereas (ii) other anonymous processes are subject to performance optimization.
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http://dx.doi.org/10.1016/j.actpsy.2016.08.008 | DOI Listing |
J Exp Psychol Learn Mem Cogn
December 2024
Basque Center on Cognition, Brain and Language.
The present study uses event-related potentials (ERPs) to investigate lexicosemantic prediction in native speakers (L1) of English and advanced second language (L2) learners of English with Swedish as their L1. The main goal of the study was to examine whether learners recruit predictive mechanisms to the same extent as L1 speakers when a change in the linguistic environment renders prediction a useful strategy to pursue. The study, which uses a relatedness proportion paradigm adapted from Lau et al.
View Article and Find Full Text PDFCogn Neurodyn
December 2025
Image Processing Laboratory, University of Valencia, Valencia, Spain.
In recent years, substantial strides have been made in the field of visual image reconstruction, particularly in its capacity to generate high-quality visual representations from human brain activity while considering semantic information. This advancement not only enables the recreation of visual content but also provides valuable insights into the intricate processes occurring within high-order functional brain regions, contributing to a deeper understanding of brain function. However, considering fusion semantics in reconstructing visual images from brain activity involves semantic-to-image guide reconstruction and may ignore underlying neural computational mechanisms, which does not represent true reconstruction from brain activity.
View Article and Find Full Text PDFInflamm Res
January 2025
Department of Nephrology, First Affiliated Hospital of Naval Medical University, Shanghai Changhai Hospital, Shanghai, China.
Background: Chronic inflammation is well recognized as a key factor related to renal function deterioration in patients with diabetic kidney disease (DKD). Neutrophil extracellular traps (NETs) play an important role in amplifying inflammation. With respect to NET-related genes, the aim of this study was to explore the mechanism of DKD progression and therefore identify potential intervention targets.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing 100101, China.
Human activity recognition by radar sensors plays an important role in healthcare and smart homes. However, labeling a large number of radar datasets is difficult and time-consuming, and it is difficult for models trained on insufficient labeled data to obtain exact classification results. In this paper, we propose a multiscale residual weighted classification network with large-scale, medium-scale, and small-scale residual networks.
View Article and Find Full Text PDFBMC Genomics
January 2025
Department of Medical Microbiology and Infectious Diseases, Erasmus University Medical Centre (Erasmus MC), Rotterdam, The Netherlands.
Background: The Joint Programming Initiative on Antimicrobial Resistance (JPIAMR) networks 'Seq4AMR' and 'B2B2B AMR Dx' were established to promote collaboration between microbial whole genome sequencing (WGS) and antimicrobial resistance (AMR) stakeholders. A key topic discussed was the frequent variability in results obtained between different microbial WGS-related AMR gene prediction workflows. Further, comparative benchmarking studies are difficult to perform due to differences in AMR gene prediction accuracy and a lack of agreement in the naming of AMR genes (semantic conformity) for the results obtained.
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