Observers can adopt attentional control settings that regulate how their attention is drawn to salient stimuli in the environment. Do observers choose their attentional control settings voluntarily, or are they primed in a bottom-up manner based on the stimuli that the observer has recently attended and responded to (i.e., target-selection history)? In the present experiment, we tested these two accounts using a long-term memory attentional control settings paradigm, in which participants memorized images of 18 common visual objects, and then searched for those objects in a spatial blink task. Unbeknownst to participants, we manipulated priming by dividing the set of target objects into two subsets: nine objects appeared frequently as targets in the spatial blink task (frequently primed objects), and nine infrequently (infrequently primed objects). We assessed attentional capture by presenting these objects as distractors in the spatial blink task and measuring their effect on task accuracy. We found that both subsets of objects captured attention more than non-studied objects, and frequently primed objects did not capture attention more than infrequently primed objects. Moreover, a follow-up analysis revealed that all studied objects captured attention, even before those objects had appeared as targets in the spatial blink task. These findings suggest that priming through target-selection history plays little-to-no role in long-term memory attentional control settings. Rather, these findings align with a growing body of evidence that attentional control settings are primarily implemented through voluntary control.
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Sci Rep
January 2025
Support Centre for Advanced Neuroimaging (SCAN), Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
This study aims to establish an imitation task of multi-finger haptics in the context of regular grasping and regrasping processes during activities of daily living. A video guided the 26 healthy, right-handed volunteers through the three phases of the task: (1) fixation of a hand holding a cuboid, (2) observation of the sensori-motor manipulation, (3) imitation of that motor action. fMRI recorded the task; graph analysis of the acquisitions revealed the associated functional cerebral connectivity patterns.
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January 2025
HIV Unit, Hospital Civil de Guadalajara, Hospital 278, Guadalajara, 44280, Mexico, 52 3338093219.
Background: HIV continues to be a public health concern in Mexico and Latin America due to an increase in new infections, despite a decrease being observed globally. Treatment adherence is a pillar for achieving viral suppression. It prevents the spread of the disease at a community level and improves the quality and survival of people living with HIV.
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January 2025
School of Environmental Science and Engineering, Yancheng Institute of Technology, Yancheng, 224051, People's Republic of China.
MXenes, as a novel two-dimensional lamellar material, has attracted much attention. However, MXenes lamellar are prone to collapse and stacking under hydrogen bonding and interlayer van der Waals forces, which affects their electrochemical and capacitive deionization performance. A three-dimensional Ni-1,3,5-benzenetricarboxylate/TiCT (Ni-BTC/TiCT) composite electrode material was developed to enhance the electrochemical and capacitive deionization performance.
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January 2025
Institute of Physical Chemistry and Polymer Physics, Leibniz-Institut für Polymerforschung Dresden e.V. (IPF), 01069, Dresden, Germany.
Template-assisted colloidal self-assembly has gained significant attention due to its flexibility and versatility. By precisely controlling the shape of the template, it is possible to achieve custom-designed nanoparticle assemblies. However, a major challenge remains in fabricating these templates over large areas at a low cost.
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January 2025
School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing, 100055, China.
Air pollution is a critical global environmental issue, further exacerbated by rapid industrialization and urbanization. Accurate prediction of air pollutant concentrations is essential for effective pollution prevention and control measures. The complex nature of pollutant data is influenced by fluctuating meteorological conditions, diverse pollution sources, and propagation processes, underscores the crucial importance of the spatial and temporal feature extraction for accurately predicting air pollutant concentrations.
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