Selective attention to relevant targets has been shown to depend on the availability of working memory (WM). Under conditions of high WM load, processing of irrelevant distractors is enhanced. Here we showed that this detrimental effect of WM load on selective attention efficiency is reversed when the task requires global- rather than local-level processing. Participants were asked to attend to either the local or the global level of a hierarchical Navon stimulus while keeping either a low or a high load in WM. In line with previous findings, during attention to the local level, distractors at the global level produced more interference under high than under low WM load. By contrast, loading WM had the opposite effect of improving selective attention during attention to the global level. The findings demonstrate that the impact of WM load on selective attention is not invariant, but rather is dependent on the level of the to-be-attended information.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.3758/s13414-012-0357-1 | DOI Listing |
J Imaging Inform Med
January 2025
Department of Anesthesiology, E-Da Cancer Hospital, I-Shou University, Kaohsiung, Taiwan.
Parkinson's disease (PD), a degenerative disorder of the central nervous system, is commonly diagnosed using functional medical imaging techniques such as single-photon emission computed tomography (SPECT). In this study, we utilized two SPECT data sets (n = 634 and n = 202) from different hospitals to develop a model capable of accurately predicting PD stages, a multiclass classification task. We used the entire three-dimensional (3D) brain images as input and experimented with various model architectures.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Computer Science Department, University of Geneva, Geneva, Switzerland.
Accurate wound segmentation is crucial for the precise diagnosis and treatment of various skin conditions through image analysis. In this paper, we introduce a novel dual attention U-Net model designed for precise wound segmentation. Our proposed architecture integrates two widely used deep learning models, VGG16 and U-Net, incorporating dual attention mechanisms to focus on relevant regions within the wound area.
View Article and Find Full Text PDFSci Rep
January 2025
Institute of Dendrology, Polish Academy of Sciences, Parkowa 5, Kórnik, 62-035, Poland.
Genetic diversity is crucial to secure the survival and sustainability of ecosystems. Given anthropogenic pressure, as well as the projected alterations connected with the level and circulation of water, riparian forests are of particular concern. In this paper, we assessed the genetic variation of black poplar - one of the keystone tree species of riverine forests.
View Article and Find Full Text PDFSci Rep
January 2025
Nanning Center for Disease Control and Prevention, Nanning, 530021, Guangxi, China.
Nowadays rice has become one of the world's staple foods. Rice in southern China is also a staple food for everyone, however, with the development of China's industrialization model, many industrial areas may be contaminated by heavy metals, leading to contamination of the agricultural areas. With the development of recent years, Nanning has become a heavily industrial development area, and rice is also a favourite staple food.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!