Despite all the major advancements in our information age, the world's most complex supercomputer is still the human brain. We may not have tri-gate 3D transistors or the ability to parse information like Watson, but our brains work in ways that computers simply can't. Of course, that could just be because science isn't there yet.
Scientists are making a headway though, as researchers at Yale and the University of Texas are afflicting computers with symptoms of schizophrenia in an effort to better the understanding of the human mind.
One theory about schizophrenia is that the brain loses the ability to forget or ignore information that's largely irrelevant. Without this filter, the brain is unable to extract meaningfulness out of experiences. Scientists are using this hypothesis in its computer model called DISCERN which could mimic schizophrenia.
"The hypothesis is that dopamine encodes the importance-the salience-of experience," says Uli Grasemann, a graduate student in the Department of Computer Science at The University of Texas at Austin. "When there's too much dopamine, it leads to exaggerated salience, and the brain ends up learning from things that it shouldn't be learning from."
"It's an important mechanism to be able to ignore things," says Grasemann. "What we found is that if you crank up the learning rate in DISCERN high enough, it produces language abnormalities that suggest schizophrenia."
"Information processing in neural networks tends to be like information processing in the human brain in many ways," says Grasemann. "So the hope was that it would also break down in similar ways. And it did."