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A new new brain imaging system that can identify a subject's simple thoughts may lead to clearer diagnoses for Alzheimer's disease or schizophrenia - as well as possibly paving the way for reading people's minds. Michael Greicius at Stanford University in California and colleagues used functional magnetic resonance imaging (fMRI) to identify patterns of brain activity associated with different mental states. He asked 14 volunteers to do one of four tasks: sing songs silently to themselves; recall the events of the day; count backwards in threes; or simply relax. Participants were given a 10-minute period during which they had to do this. For the rest of that time they were free to think about whatever they liked. The participants' brains were scanned for the entire 10 minutes, and the patterns of connectivity associated with each task were teased out by computer algorithms that compared scans from several volunteers doing the same task. This differs from previous experiments, in which the subjects were required to perform mental activities at specific times and the scans were then compared with brain activity when they were at rest. Greicius reasons his method encourages "natural" brain activity more like that which occurs in normal thought.

Center for Computer Research in Music and Acoustics

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We are offering this course on Natural Language Processing free and online to students worldwide, January - March 2012, continuing Stanford's exciting forays into large scale online instruction. Students have access to screencast lecture videos, are given quiz questions, assignments and exams, receive regular feedback on progress, and can participate in a discussion forum. Those who successfully complete the

ConvNetJS is a Javascript library for training Deep Learning models (mainly Neural Networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat.