Nematoduino: A Roundworm Neural Model on an Arduino

When it comes to building a neural network to simulate complex behavior, Arduino isn’t exactly the first platform that springs to mind. But when your goal is to model the behavior of an organism with only a handful of neurons, the constraints presented by an Arduino start to make sense.

It may be the most important non-segmented worm you’ve never heard of, but Caenorhabditis elegans, mercifully abbreviated C. elegans, is an important model organism for neurobiology, having had its entire nervous system mapped in 2012. [Nathan Griffith] used this “connectome” to simulate a subset of the diminutive nematode’s behaviors, specifically movements toward attractants and away from obstacles. Riding atop a small robot chassis, the Arduino sends signals to the motors when the model determines it’s time to fire the virtual worm’s muscles. An ultrasonic sensor stands in for the “nose touch” neurons of the real worm, and when the model is not busy avoiding a touch, it’s actively seeking something to eat using the “chemotaxis” behavior. The model is up on GitHub and [Nathan] hopes it provides an approachable platform for would-be neuroroboticists.

This isn’t the first time someone has modeled the nematode’s connectome in silico, but kudos to [Nathan] for accomplishing it within the constraints an Arduino presents.

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Gift Your Next Robot With the Brain of a Roundworm

A group of developers called [OpenWorm] have mapped the 302 neurons of the Caenorhabditis elegans species of roundworm and created a virtual neural network that can be used to solve all the types of problems a worm might encounter. Which, when you think about it, aren’t much different from those a floor-crawling robots would be confronted with.

wormy

In a demo video released by one of the projects founders, [Timothy Busbice], their network is used to control a small Lego-rover equipped with a forward sonar sensor. The robot is able to stop before it hits a wall and determine an appropriate response, which may be to stop, back up, or turn. This is all pretty fantastic when you compare these 302 neural connections to any code you’ve ever written to accomplish the same task! It might be a much more complex route to the same outcome, but its uniquely organic… which makes watching the little Lego-bot fascinating; its stumbling around even looks more like thinking than executing.

I feel obligated to bring up the implications of this project. Since we’re all thinking about it now, let’s all imagine the human brain similarly mapped and able to simulate complex thought processes. If we can pull this off one day, not only will we learn a lot more about how our squishy grey hard drives process information, artificial intelligence will also improve by leaps and bounds. An effort to do this is already in effect, called the connectome project, however since there are a few more connections to map than with the c. elegans’ brain, it’s a feat that is still underway.

The project is called “open”worm, which of course means you can download the code from their website and potentially dabble in neuro-robotics yourself. If you do, we want to hear about your wormy brain bot.

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