error rates under 1%, significantly better than other recent methods. In order to better attract users to this new form of security the team is still researching mental tasks that are enjoyable for the user to perform while having their brainwaves identified. In the future this method could be as cheap, accessible, and straightforward as thought itself. John-Dylan Haynes states that fMRI can also be used to identify recognition in the brain. He provides the example of a criminal being interrogated about whether he recognizes the scene of the crime or murder weapons. Methods of analysis Classification In classification, a pattern of activity across multiple voxels is used to determine the particular class from which the stimulus was drawn. Many studies have classified visual stimuli, but this approach has also been used to classify cognitive states. Reconstruction In reconstruction brain reading the aim is to create a literal picture of the image that was presented. Early studies used voxels from early visual cortex areas (V1, V2, and V3) to reconstruct geometric stimuli made up of flickering checkerboard patterns. EEG EEG has also been used to identify recognition of specific information or memories by the P300 event related potential, which has been dubbed 'brain fingerprinting'. Accuracy Brain-reading accuracy is increasing steadily as the quality of the data and the complexity of the decoding algorithms improve. In one recent experiment it was possible to identify which single image was being seen from a set of 120. In another it was possible to correctly identify 90% of the time which of two categories the stimulus came and the specific semantic category (out of 23) of the target image 40% of the time. Limitations It has been noted that so far brain-reading is limited. "In practice, exact reconstructions are impossible to achieve by any reconstruction algorithm on the basis of brain activity signals acquired by fMRI. This is because all reconstructions will inevitably be limited by inaccuracies in the encoding models and noise in the measured signals. Our results demonstrate that the natural image prior is a powerful (if unconventional) tool for mitigating the effects of these fundamental limitations. A natural image prior with only six million images is sufficient to produce reconstructions that are structurally and semantically similar to a target image." Ethical issues With brain scanning technology becoming increasingly accurate, experts predict important debates over how and when it should be used.