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The project was inspired by the 2023 field trip to caspian sea during the YEMAA Artist Residency where Laura Rodriguez participated as a mentor of Bioart practices in Atyrau Kazakhstan.

This speculative art project envisions a future where humans evolve to thrive in an increasingly aquatic world. Inspired by the lateral line system of the Caspian roach, the artist proposes wearable, bio-inspired organs that enhance underwater navigation and sensory perception.

The project speculates in how cells from the lateral  line of marine organism could grow over human morphology to produce a symbiotic organ to navigate underwater.

 

The lateral line, also called the lateral line organ (LLO), and it is a system of sensory organs found in fish and amphibians, used to detect movement, vibration, and pressure in the surrounding water to navigate underwater. 

This organ sense the pattern of water flow over their body surface via mechanosensory organs called neuromasts, which are distributed in a characteristic pattern over the body surface.

 

The project works with models of neuromast growing over the human vertebras. 
 

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Copy Rights. Laura Rodriguez 
 

The project is presented in a sci-fi medical approach on the top of a medical metallic table, and as possible past with the fossils of this organs in the bottom part of the installation playing with the possible future or speculative past of evolutionary game. 

Through this work, the artist explores the boundaries between human and nature, technology and biology. The project responds to the real-world context of flooding in Atyrau, Kazakhstan, suggesting a radical approach to environmental adaptation and invites viewers to contemplate a posthuman future where our bodies evolve into technological and directed symbiosis with aquatic ecosystems.

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The artwork was complemented with AI models built with photographies underwater and the obtained 3D models from computational growth. The photographies and models were brought together in Blender and then feed into motion generation neural networks.

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