Olfactory learning may allow insects to forage optimally by more efficiently finding and using favourable food sources. Although olfactory learning has been shown in bees, insect herbivores and parasitoids, there are fewer examples from polyphagous predators. In this study, olfactory learning by a predatory coccinellid beetle is reported for the first time. In laboratory trials, adults of the aphidophagous ladybird Coccinella septempunctata did not prefer the odour of one aphid-infested barley cultivar over another. However, after feeding on aphids for 24 h on a cultivar, they preferred the odour of that particular cultivar. The mechanism appeared to be associative learning rather than sensitisation. Although inexperienced ladybirds preferred the odour of an aphid-infested barley cultivar over uninfested plants of the same cultivar, after feeding experience on a different cultivar this preference disappeared. This may indicate the acquisition and replacement of olfactory templates. The odour blends of the different aphid-infested barley cultivars varied qualitatively and quantitatively, providing a potential basis for olfactory discrimination by the ladybird. The results show that predatory coccinellids can learn to associate the odour of aphid-infested plants with the presence of prey, and that this olfactory learning ability is sensitive enough to discriminate variability between different genotypes of the same plant.
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http://dx.doi.org/10.1007/s00442-010-1892-x | DOI Listing |
Biological memory networks are thought to store information by experience-dependent changes in the synaptic connectivity between assemblies of neurons. Recent models suggest that these assemblies contain both excitatory and inhibitory neurons (E/I assemblies), resulting in co-tuning and precise balance of excitation and inhibition. To understand computational consequences of E/I assemblies under biologically realistic constraints we built a spiking network model based on experimental data from telencephalic area Dp of adult zebrafish, a precisely balanced recurrent network homologous to piriform cortex.
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January 2025
Laboratorio de Insectos Sociales, Departamento de Biodiversidad y Biología Experimental, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.
Recently, it has been shown that sugar‑conditioned honey bees can be biased towards a nectarless dioecious crop as kiwifruit. The challenges for an efficient pollination service in this crop species are its nectarless flowers and its short blooming period. It is known that combined non-sugar compounds (NSCs) present in the floral products of different plants, such as caffeine and arginine, enhance olfactory memory retention in honey bees.
View Article and Find Full Text PDFBrain Res Bull
January 2025
School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou 511442, China; Guangdong Province Key Laboratory of Biomedical Engineering, South China University of Technology, Guangzhou 510006, China; Department of Aging Research and Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan. Electronic address:
The methodology of machine learning with multi-omics data has been widely adopted in the discriminative analyses of schizophrenia, but most of these studies ignored the cooperative interactions and topological attributes of multi-omics networks. In this study, we constructed three types of brain graphs (BGs), three types of gut graphs (GGs), and nine types of brain-gut combined graphs (BGCGs) for each individual. We proposed a novel methodology of multi-omics graph convolutional network (MO-GCN) with an attention mechanism to construct a classification model by integrating all BGCGs.
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January 2025
School of Agriculture, Food and Ecosystem Sciences, Faculty of Science, The University of Melbourne, Parkville, VIC, 3010, Australia.
Due to the diverse climate in Iran, there has been an opportunity for the emergence of different domestic sheep breeds. On the other hand, two of the seven wild sheep species have settled in the broad areas of Iran. This study investigated the introgression between wild and domestic Iranian sheep using the whole genome sequencing data for 55 domestic and 19 wild sheep.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Computer Science, Louisiana Tech University, 201 Mayfield Ave, Ruston, LA 71272, USA.
Odor source localization (OSL) technology allows autonomous agents like mobile robots to localize a target odor source in an unknown environment. This is achieved by an OSL navigation algorithm that processes an agent's sensor readings to calculate action commands to guide the robot to locate the odor source. Compared to traditional 'olfaction-only' OSL algorithms, our proposed OSL algorithm integrates vision and olfaction sensor modalities to localize odor sources even if olfaction sensing is disrupted by non-unidirectional airflow or vision sensing is impaired by environmental complexities.
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