Can Drosophila melanogaster tell who's who?
| Autor: | Joel D. Levine, Nihal Murali, Jonathan Schneider, Graham W. Taylor |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Male Photoreceptors Sensory Receptors genetic structures Computer science Vision Physiology Visual System Sensory Physiology Visual Acuity lcsh:Medicine Social Sciences Convolutional neural network Machine Learning Animal Cells Melanogaster Medicine and Health Sciences Human Performance Psychology lcsh:Science Cognitive science Neurons Multidisciplinary biology Drosophila Melanogaster Eukaryota Animal Models Sensory Systems Semantics Insects Experimental Organism Systems Female Drosophila Sensory Perception Drosophila melanogaster Cellular Types Research Article Signal Transduction Arthropoda Research and Analysis Methods Models Biological 03 medical and health sciences Model Organisms Similarity (psychology) Animals Behavior lcsh:R fungi Organisms Biology and Life Sciences Afferent Neurons Linguistics Cell Biology biology.organism_classification Invertebrates eye diseases 030104 developmental biology Cellular Neuroscience Animal Studies lcsh:Q Visual learning Neuroscience |
| Zdroj: | PLoS ONE PLoS ONE, Vol 13, Iss 10, p e0205043 (2018) |
| ISSN: | 1932-6203 |
| Popis: | Drosophila melanogaster are known to live in a social but cryptic world of touch and odours, but the extent to which they can perceive and integrate static visual information is a hotly debated topic. Some researchers fixate on the limited resolution of D. melanogaster's optics, others on their seemingly identical appearance; yet there is evidence of individual recognition and surprising visual learning in flies. Here, we apply machine learning and show that individual D. melanogaster are visually distinct. We also use the striking similarity of Drosophila's visual system to current convolutional neural networks to theoretically investigate D. melanogaster's capacity for visual understanding. We find that, despite their limited optical resolution, D. melanogaster's neuronal architecture has the capability to extract and encode a rich feature set that allows flies to re-identify individual conspecifics with surprising accuracy. These experiments provide a proof of principle that Drosophila inhabit a much more complex visual world than previously appreciated. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|