Spiders are highly skilled builders, precisely weaving strands to create a 3D web that serves as their home and a preying ground. Now, a team of researchers has created music by translating the structure of a spider web.
“The spider lives in an environment of vibrating strings,” says Markus Buehler, Ph.D., and the project’s principal investigator. “They don’t see very well, so they sense their world through vibrations, which have different frequencies.” These vibrations occur when the spider weaves a silk strand during the building or when a trapped insect moves the web.
Buehler always wondered if he could extract music from non-human sources such as spider webs. “Webs could be a new source for musical inspiration that is very different from the usual human experience,” he said.
During the study, Buehler and his MIT colleagues scanned a natural spider web with a laser to capture 2D cross-sections. They reconstructed the web’s 3D network by using sophisticated computer algorithms. Every strand of the web was assigned a different frequency of sound, allowing them to create notes that were later combined in patterns based on the web’s 3D structure and create melodies.
The team then created a harp-like instrument and played spider web music during several live performances across the world. Not just that! They also made a VR setup where people can visually and audibly feel the web.
“The virtual reality environment is really intriguing because your ears are going to pick up structural features that you might see but not immediately recognize,” Buehler said. “By hearing it and seeing it at the same time, you can really start to understand the environment the spider lives in.”
Besides, the researchers also explored how the sound of the web changes when exposed to different mechanical forces like stretching. The team also tried understanding how to communicate with spiders in their language. They recorded web vibrations produced when spiders performed activities such as building or communicating with other spiders.
While the frequencies sounded similar, a machine learning algorithm classified the sounds into different activities.
