Artificial Intelligence: AI Analyzes How Spiders Construct Their Webs

November 15, 2021 | Artificial Intelligence, News
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How do these tiny creatures with even tinier brains create their webs of such geometrical precision and elegance?

Researchers at the Krieger School at John Hopkins University used night vision and AI to unravel the secret methods that spiders use to create their webs in the dark. Their findings are due to publish in the November issue of Current Biology. (John Hopkins University HUB)

Senior author Andrew Gordus, a behavioral biologist in the Department of Biology in the Krieger School of Arts and Sciences, said in the context of these spectacular webs that “this is even more amazing because a spider’s brain is so tiny and I was frustrated that we didn’t know more about how this remarkable behavior occurs.”

The researchers have now defined the entire web building “choreography” in a web-building algorithm, or playbook. What is amazing is that the spiders construct the delicately precise and geometrical webs in the dark, without vision, and entirely through their sense of touch.

John Hopkins research on spiders’ web-making: how they did it

In a never before attempt, the John Hopkins researchers set out to document and analyze the web-building behaviour and motor actions of the fingertip-sized hackled orb spider. The researchers recorded the web-building activities of six of these spiders using infrared cameras, infrared lights, and specialized machine vision software. That software could detect the posture of the spider, frame by frame, in order to document all the leg movements that build the web.

The set up recorded millions of individual leg actions, and the upshot of it was that the spiders basically used the same web-building methods.

“They’re all using the same rules, which confirms the rules are encoded in their brains,” said Gorbus. “Now we want to know how those rules are encoded at the level of neurons.”

“The spider is fascinating because here you have an animal with a brain built on the same fundamental building blocks as our own, and this work could give us hints on how we can understand larger brain systems, including humans, and I think that’s very exciting,” said lead author Abel Corver, a graduate student studying web-making and neurophysiology at John Hopkins.

Related Story: Machine Learning To Identify Whale Sounds, Warn Ships

Image Credit: Flickr

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