A group of neuroscientists and software engineers at the University of Waterloo in Canada are claiming to have built the world’s most complex, large-scale model simulation of the human brain. The simulated brain, which runs on a supercomputer, has a digital eye which it uses for visual input, a robotic arm that it uses to draw its responses — and it can pass the basic elements of an IQ test.

The brain, called Spaun (Semantic Pointer Architecture Unified Network), consists of 2.5 million simulated neurons, allowing it to perform eight different tasks. These tasks range from copy drawing to counting, to question answering and fluid reasoning. At this point, you should watch the video below to get a rough idea of how Spaun works — and then read on to find out why Spaun is so interesting.

Now, the nitty-gritty details. Spaun has a 28×28 (784-pixel) digital eye, and a robotic arm which can write on some paper. Every interaction with Spaun is through its 784-pixel eye. The scientists flash up a bunch of numbers and letters, which Spaun reads into memory, and then another letter or symbol acts as the command, telling Spaun what to do with its memory. The output of the task is then inscribed by the robotic arm.

Spaun’s brain consists of 2.5 million neurons that are broken down into a bunch of simulated cranial subsystems, including the prefrontal cortex, basal ganglia, and thalamus, which are wired together with simulated neurons that very accurately mimic the wiring of a real human brain. The basic idea is that these subsystems behave very similarly to a real brain: Visual input is processed by the thalamus, the data is stored in the neurons, and then the basal ganglia fires off a task to a part of the cortex that’s designed to handle that task.

All of this computation is performed in a physiologically accurate way, with simulated voltage spikes and neurotransmitters. Even the limitations of the human brain are simulated, as you can see in the video below, with Spaun struggling to store more than a few numbers in its short-term memory.

The end result is a brain that is mechanistically simple (2.5 million neurons isn’t really much to write home about), but which is surprisingly flexible. By implementing just a handful of very basic tasks, it’s interesting to see how complex behavior begins to emerge. There are some tantalizing hints as to how the brain evolved: starting with simple tasks, and then building upon and weaving them together to build complex functionality. In the video below, Spaun recognizes the pattern of a number sequence — the kind of question you would find on an actual IQ test.

Moving forward, the research team, led by Chris Eliasmith, wants to imbue Spaun with adaptive plasticity — the ability to rewire its neurons and learn new tasks simply by doing, rather than being pre-programmed. As for the ultimate end goal, Eliasmith is excited about Spaun’s prospects. “It lets us understand how the brain, the biological substrate, and behavior relate. That’s important for all sorts of health applications,” he says in an interview with PopSci. In testing he has “killed” synthetic neurons and watched performance degrade, which could provide an interesting insight into natural aging and degenerative disorders.

Spaun is built upon Nengo, a graphical open-source software package for building simulated neural systems. You can actually download the Spaun neural model, if you want to simulate your own brain — though I suspect it might require a little more processing power than your desktop PC.

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Research paper: DOI: 10.1126/science.1225266 – “A Large-Scale Model of the Functioning Brain”