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Despite the importance of an observer's goals in determining how a visual object is categorized, surprisingly little is known about how humans process the task context in which objects occur and how it may interact with the processing of objects. Using magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI) and multivariate techniques, we studied the spatial and temporal dynamics of task and object processing. Our results reveal a sequence of separate but overlapping task-related processes spread across frontoparietal and occipitotemporal cortex. Task exhibited late effects on object processing by selectively enhancing task-relevant object features, with limited impact on the overall pattern of object representations. Combining MEG and fMRI data, we reveal a parallel rise in task-related signals throughout the cerebral cortex, with an increasing dominance of task over object representations from early to higher visual areas. Collectively, our results reveal the complex dynamics underlying task and object representations throughout human cortex.
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http://dx.doi.org/10.7554/eLife.32816 | DOI Listing |
Cortex
August 2025
Experimental Psychology and Methods, Universität Leipzig, Leipzig, Germany. Electronic address:
Effects of location- and object-based attention on sensory processing have been mostly studied in isolation leaving the relations between them less well understood. In an EEG experiment, temporal dynamics of location- and object-based attention were investigated with a probabilistic spatial cueing task to test temporal differences between sensory enhancement of two locations in one object. Stimuli consisted of two vertical rectangles/bars filled with a random noise pattern.
View Article and Find Full Text PDFCogn Psychol
September 2025
Graduate School of Engineering, Kochi University of Technology, Kami, Kochi, Japan. Electronic address:
Prior researches on global-local processing have focused on hierarchical objects in the visual modality, while the real-world involves multisensory interactions. The present study investigated whether the simultaneous presentation of auditory stimuli influences the recognition of visually hierarchical objects. We added four types of auditory stimuli to the traditional visual hierarchical letters paradigm:no sound (visual-only), a pure tone, a spoken letter that was congruent with the required response (response-congruent), or a spoken letter that was incongruent with it (response-incongruent).
View Article and Find Full Text PDFAdv Mater
September 2025
Departmant of Materials Science and Engineering, Seoul National University, Seoul, 08826, Republic of Korea.
Microrobots are expected to push the boundaries of robotics by enabling navigation in confined and cluttered environments due to their sub-centimeter scale. However, most microrobots perform best only in the specific conditions for which they are designed and require complete redesign and fabrication to adapt to new tasks and environments. Here, fully 3D-printed modular microrobots capable of performing a broad range of tasks across diverse environments are introduced.
View Article and Find Full Text PDFPLoS Comput Biol
September 2025
Department of Human Behaviour, Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.
A major goal of behavioural ecology is to explain how phenotypic and ecological factors shape the networks of social relationships that animals form with one another. This inferential task is notoriously challenging. The social networks of interest are generally not observed, but must be approximated from behavioural samples.
View Article and Find Full Text PDFPLoS One
September 2025
Symbiosis Institute of Technology, Symbiosis International University, Pune, India.
With the rapid development of industrial automation and intelligent manufacturing, defect detection of electronic products has become crucial in the production process. Traditional defect detection methods often face the problems of insufficient accuracy and inefficiency when dealing with complex backgrounds, tiny defects, and multiple defect types. To overcome these problems, this paper proposes Y-MaskNet, a multi-task joint learning framework based on YOLOv5 and Mask R-CNN, which aims to improve the accuracy and efficiency of defect detection and segmentation in electronic products.
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