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- W51326844 abstract "This report summarizes the modeling challenge held in conjunction with the International Conference on Artificial Neural Networks (ICANN) 2011 and sponsored by the PASCAL2 Challenge Programme. The challenge aimed at promoting awareness of the task “mind reading” or “brain decoding” based on magnetoencephalography (MEG) data. For neuroscientists, the task provides a practical tool for understanding brain process underlying perception, since any mechanism that can be used for inferring the stimulus on the basis of brain activity must be related to processing of the stimulus. For machine learners and other modelers, the challenge provides an interesting real-world application playground for solving active machine learning problems such as multi-view learning and covariate shift. The task was to infer from one-second time windows the type of visual stimulus shown to the subject. The best brain decoders, out of the 10 submissions, reached almost 70% accuracy in the task with mere 23% chancelevel, proving that even a short MEG measurement can be sufficient for brain decoding tasks with a reasonable number of stimulus categories." @default.
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- W51326844 date "2012-01-01" @default.
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- W51326844 title "ICANN/PASCAL2 Challenge: MEG Mind Reading — Overview and Results" @default.
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