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Toward Real-Time Animal Tracking with Integrated Stimulus Control for Automated Conditioning in Aquatic Eco-Neurotoxicology.
Bai, Yutao; Henry, Jason; Cheng, Eva; Perry, Stuart; Mawdsley, David; Wong, Bob B M; Kaslin, Jan; Wlodkowic, Donald.
Afiliación
  • Bai Y; The Neurotoxicology Laboratory, School of Science, RMIT University, Melbourne, VIC 3083, Australia.
  • Henry J; The Neurotoxicology Laboratory, School of Science, RMIT University, Melbourne, VIC 3083, Australia.
  • Cheng E; Faculty of Engineering and IT, School of Electrical and Data Engineering, University of Technology Sydney, Sydney, NSW 2007, Australia.
  • Perry S; Faculty of Engineering and IT, School of Electrical and Data Engineering, University of Technology Sydney, Sydney, NSW 2007, Australia.
  • Mawdsley D; Defence Science and Technology Group, Melbourne, VIC 3207, Australia.
  • Wong BBM; School of Biological Sciences, Monash University, Melbourne, VIC 3800, Australia.
  • Kaslin J; Australian Regenerative Medicine Institute, Monash University, Melbourne, VIC 3800, Australia.
  • Wlodkowic D; The Neurotoxicology Laboratory, School of Science, RMIT University, Melbourne, VIC 3083, Australia.
Environ Sci Technol ; 57(48): 19453-19462, 2023 Dec 05.
Article en En | MEDLINE | ID: mdl-37956114
Aquatic eco-neurotoxicology is an emerging field that requires new analytical systems to study the effects of pollutants on animal behaviors. This is especially true if we are to gain insights into one of the least studied aspects: the potential perturbations that neurotoxicants can have on cognitive behaviors. The paucity of experimental data is partly caused by a lack of low-cost technologies for the analysis of higher-level neurological functions (e.g., associative learning) in small aquatic organisms. Here, we present a proof-of-concept prototype that utilizes a new real-time animal tracking software for on-the-fly video analysis and closed-loop, external hardware communications to deliver stimuli based on specific behaviors in aquatic organisms, spanning three animal phyla: chordates (fish, frog), platyhelminthes (flatworm), and arthropods (crustacean). The system's open-source software features an intuitive graphical user interface and advanced adaptive threshold-based image segmentation for precise animal detection. We demonstrate the precision of animal tracking across multiple aquatic species with varying modes of locomotion. The presented technology interfaces easily with low-cost and open-source hardware such as the Arduino microcontroller family for closed-loop stimuli control. The new system has potential future applications in eco-neurotoxicology, where it could enable new opportunities for cognitive research in diverse small aquatic model organisms.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Artrópodos / Programas Informáticos Límite: Animals Idioma: En Revista: Environ Sci Technol Año: 2023 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Artrópodos / Programas Informáticos Límite: Animals Idioma: En Revista: Environ Sci Technol Año: 2023 Tipo del documento: Article País de afiliación: Australia