Brain Design with Neurorobots
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Brain Design with Neurorobots

Can robots think and feel? Can they have minds? Can they learn to be more like us? To do any of this, robots need brains. Scientists use “neurorobots” – robots with computer models of biological brains – to understand everything from motor control, and navigation to learning and problem solving. At Backyard Brains, we are working hard to take neurorobots out of the research labs and into the hands of anyone who wants one. How would you like a robot companion with life-like habits and goals? Even better, how would you like to visualize and rebuild its brain in real-time? Now that’s neuroscience made real!

I’m Christopher Harris, a neuroscientist from Sweden who for the past few years have had a bunch of neurorobots exploring my living room floor. Last year I joined Backyard Brains to turn my brain-based rugrats into a new education technology that makes it possible for high-school students to learn neuroscience by designing neurorobot brains. Our robots have cameras, wheels, microphones and speakers, and students use a drag-and-drop interface to hook them all up with neurons and neural networks into an artificial brain. Needless to say, the range of brains and behaviors you can create is limitless! Twice already we’ve had the opportunity to pilot our neurorobots with some awesome high-school students, and we’re learning a ton about how to make brain design a great learning experience.

But hang on, is this just machine learning (ML) dressed up to look like neuroscience? Not at all. Although ML algorithms and biological brains both get their power from connecting lots of neurons into networks that learn and improve over time, there are also crucial differences. Biological neurons are complex and generate spontaneous activity, while ML neurons are silent in the absence of input. Unlike ML networks, biological brain models are ideally suited for “neuromorphic” hardware, which has extraordinary properties, including (some say) the ability to support consciousness. Finally, while ML networks are organized into neat symmetrical layers with only the occasional feedback-loop, biological brains contain a huge diversity of network structures connected by tangles of criss-crossing nerve fibres. Personally I’m a big fan of the brain’s reward system – the sprawling, dopamine-driven network that generates our attention, motivation, decision-making and learning. So rest assured, fellow reward-enthusiasts, our neurorobots have a big bright “reward button” to release dopamine into the artificial brain, reinforce its synapses and shape its personality.

Interested? If you’d like to take part in a workshop to learn brain design for neurorobots, or if you’re a teacher and would like Backyard Brains to come and give your students a hands-on learning experience they’ll never forget; please email me at christopher@backyardbrains.com, and check back here for updates.


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