DeepLabStream enables closed-loop behavioral experiments using deep learning-based markerless, real-time posture detection
DeepLabStream, developed by Schweihoff and colleagues, is a deep-learning based toolkit to conduct closed-loop behavioral experiments triggered by postural expressions. The capabilities of this new toolkit are shown in an optogenetic stimulation experiment capturing activity dependent neuronal ensem...
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/0b703c96fcda4d4aacde89d962e46ac8 |
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| Sumario: | DeepLabStream, developed by Schweihoff and colleagues, is a deep-learning based toolkit to conduct closed-loop behavioral experiments triggered by postural expressions. The capabilities of this new toolkit are shown in an optogenetic stimulation experiment capturing activity dependent neuronal ensembles, as well as in an autonomously conducted conditioning task. |
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