Bees navigate in complex environments using visual, olfactory and mechano-sensorial cues. In the lowest region of the atmosphere, the wind environment can be highly unsteady and bees employ fine motor-skills to enhance flight control. Recent work reveals sophisticated multi-modal processing of visual and olfactory channels by the bee brain to enhance foraging efficiency, but it currently remains unclear whether wind-induced mechano-sensory inputs are also integrated with visual information to facilitate decision making. Individual honeybees were trained in a linear flight arena with appetitive-aversive differential conditioning to use a context-setting cue of 3 m s cross-wind direction to enable decisions about either a 'blue' or 'yellow' star stimulus being the correct alternative. Colour stimuli properties were mapped in bee-specific opponent-colour spaces to validate saliency, and to thus enable rapid reverse learning. Bees were able to integrate mechano-sensory and visual information to facilitate decisions that were significantly different to chance expectation after 35 learning trials. An independent group of bees were trained to find a single rewarding colour that was unrelated to the wind direction. In these trials, wind was not used as a context-setting cue and served only as a potential distracter in identifying the relevant rewarding visual stimuli. Comparison between respective groups shows that bees can learn to integrate visual and mechano-sensory information in a non-elemental fashion, revealing an unsuspected level of sensory processing in honeybees, and adding to the growing body of knowledge on the capacity of insect brains to use multi-modal sensory inputs in mediating foraging behaviour.
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http://dx.doi.org/10.1242/jeb.142679 | DOI Listing |
J Mol Neurosci
January 2025
Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, China.
Hemorrhagic stroke is a known complication of glioma, yet the underlying mechanisms remain poorly understood. This study aims to investigate key biomarkers of glioma-related hemorrhage to provide insights into glioma molecular therapies. Data were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases to analyze differentially expressed genes (DEGs) in glioma by contrasting glioblastoma (GBM) with low-grade gliomas (LGGs).
View Article and Find Full Text PDFChin J Integr Med
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Digestive Endoscopy, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning Province, 116000, China.
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Transl Vis Sci Technol
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Department of Biomedical Engineering, Duke University, Durham, NC, USA.
The introduction of optical coherence tomography (OCT) in the 1990s revolutionized diagnostic ophthalmic imaging. Initially, OCT's role was primarily in the adult ambulatory ophthalmic clinics. Subsequent advances in handheld form factors, integration into surgical microscopes, and robotic assistance have expanded OCT's utility and impact outside of its initial environment in the adult outpatient ophthalmic clinic.
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Biosecurity, Los Alamos National Laboratory, Los Alamos, NM, United States.
Research typically promotes two types of outcomes (inventions and discoveries), which induce a virtuous cycle: something suspected or desired (not previously demonstrated) may become known or feasible once a new tool or procedure is invented and, later, the use of this invention may discover new knowledge. Research also promotes the opposite sequence-from new knowledge to new inventions. This bidirectional process is observed in geo-referenced epidemiology-a field that relates to but may also differ from spatial epidemiology.
View Article and Find Full Text PDFGROUP ACM SIGCHI Int Conf Support Group Work
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College of Information Sciences and Technology, The Pennsylvania State University, University Park, Pennsylvania, USA.
Assistive technologies for people with visual impairments (PVI) have made significant advancements, particularly with the integration of artificial intelligence (AI) and real-time sensor technologies. However, current solutions often require PVI to switch between multiple apps and tools for tasks like image recognition, navigation, and obstacle detection, which can hinder a seamless and efficient user experience. In this paper, we present NaviGPT, a high-fidelity prototype that integrates LiDAR-based obstacle detection, vibration feedback, and large language model (LLM) responses to provide a comprehensive and real-time navigation aid for PVI.
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