![\"MEG](\"http://nilab.cimec.unitn.it/people/olivetti/decmeg2014/MEG_data2.png\")
The training data consist of 9414 trials, i.e. MEG recordings and the class labels (Face/Scramble), from 16 subjects (subject01 to subject16). The test set comprises 4058 MEG recordings from 7 subjects (subject17 to subject23), without class labels. For each subject approximately 580-590 trials are available. Each trial consists of 1.5 seconds of MEG recording (starting 0.5sec before the stimulus starts) and the related class label, Face (class 1) or Scramble (class 0) . The data were down-sampled to 250Hz and high-pass filtered at 1Hz. 306 timeseries were recorded, one for each of the 306 channels, for each trial. All the pre-processing steps were carried out with mne-python. The trials of each subject are arranged into a 3D data matrix (trial x channel x time) of size 580 x 306 x 375. For each subject in the train set, the 3D data matrix and the associated vector of 580 class labels are saved into a file named train_subjectXX.mat. The data of the subjects in the test set are saved in files named test_subjectXX.mat. These files are in Matlab v5.0 format and can be easily read from Octave/Matlab, Python (see scipy.io.loadmat()), R (see the R.matlab package), Java (see JMatIO) and from other programming languages.
\r\nNotice that the all train and test files are conveniently grouped into 4 large zip files: train_01_06.zip, train_07_12.zip, train_13_16.zip and test_17_23.zip.
\r\nThe MEG sensors are spatially arranged as described in the file Vectorview-mag.lout, which is a 2D approximation of the actual layout (see the picture in the description page). The 306 sensors are grouped, three at a time, in 102 locations. At each location two orthogonal gradiometers and one magnetometer record the magnetic field induced by the brain currents. The magnetometer measures the z (radial) component of the magnetic field, while the gradiometers measure the x and y spatial derivative of the magnetic field.
\r\nNotice that if the number in the sensor name ends with \"1\" then it is a magnetometer. If it ends with \"2\" or \"3\", then it is a gradiometer. For example, \"MEG 0113\" is a gradiometer and \"MEG 0111\" is a magnetometer.
\r\nSimple Python and Matlab code examples to load the data and to create a submission file, are available on GitHub at this link. Examples of code for other programming languages may be available in future. Contributions are welcome.
\r\nEach file train_subjectXX.mat has the following fields:
\r\nEach file test_subjectXX.mat has the same fields as above with the exception of the absence of field y and the addition of this field:
\r\nUnderstanding how the human brain works is a primary goal in neuroscience research. Non-invasive functional neuroimaging techniques, such as magnetoencephalography (MEG), are able to capture the brain activity as multiple timeseries. When a subject is presented a stimulus and the concurrent brain activity is recorded, the relation between the pattern of recorded signal and the category of the stimulus may provide insights on the underlying mental process. Among the approaches to analyse the relation between brain activity and stimuli, the one based on predicting the stimulus from the concurrent brain recording is called brain decoding.
\r\nThe goal of this competition is to predict the category of a visual stimulus presented to a subject from the concurrent brain activity. The brain activity is captured with an MEG device which records 306 timeseries at 1KHz of the magnetic field associated with the brain currents. The categories of the visual stimulus for this competition are two: face and scrambled face. A stimulus and the concurrent MEG recording is called trial and thousands of randomized trials were recorded from multiple subjects. The trials of some of the subjects, i.e. the train set, are provided to create prediction models. The remaining trials, i.e. the test set, belong to different subjects and they will be used to score the prediction models. Because of the variability across subjects in brain anatomy and in the patterns of brain activity, a certain degree of difference is expected between the data of different subjects and thus between the train set and the test set.
\r\n
Full details of the neuroscientific experiment in which the data were collected are described in:
\r\nA brief survey of the scientific literature on the problem of decoding across subjects, together with the description of the train set of this competition and a preliminary solution in terms of transfer learning, are described in:
\r\nThis competition is associated with the the 19th International Conference on Biomagnetism, Biomag 2014. The Biomag conference will be held in Halifax, Canada, August 24-28, 2014.
\r\nThis competition is organized by Emanuele Olivetti, Mostafa Kia and Paolo Avesani (NeuroInformatics Lab, Fondazione Bruno Kessler and Università di Trento, IT).
\r\nThe awards of this competition are funded by Elekta Oy, MEG International Services Ltd (MISL), Fondazione Bruno Kessler, and Besa. We would also like to thank Daniel Wakeman (Martinos Center, MGH, USA), Richard Henson (MRC/CBU, Cambridge, UK), Ole Jensen (Donders Institute, NL), Nathan Weisz (University of Trento, IT) and Alexandre Gramfort (Telecom ParisTech, CNRS, CEA / Neurospin) for their contributions in preparing this competition.
\r\n![\"Elekta](\"https://storage.googleapis.com/kaggle-media/competitions/kaggle/3641/media/elekta.jpg\")
![\"MISL](\"https://storage.googleapis.com/kaggle-media/competitions/kaggle/3641/media/CTFMEG.jpg\")
![\"Fondazione](\"https://storage.googleapis.com/kaggle-media/competitions/kaggle/3641/media/FBK.jpg\")
![\"BESA](\"https://storage.googleapis.com/kaggle-media/competitions/kaggle/3641/media/besa.png\")
The evaluation metric for this competition is prediction accuracy, i.e. the total number of correct predictions over the total size of the test set.
\r\nNotice that the (public) score on the leaderboard and the final (private) score of the competition are computed on trials from different sets of subjects. For this reason it could happen that the public score on the leaderboard may be substantially different from the final score.
\r\nThe submission file should contain two columns: Id and Prediction. The Id is a unique identifier of each trial in the test set. It is a numeric value of 5 digits where the first two are the identifier of the subject and the last three are the identifier of the trial. For example, the prediction of trial 15 for subject 22 has Id 22015. The Prediction value indicates whether the predicted value is 0 (Scramble) or 1 (Face).
\r\nThe file should contain a header and have the following format:
\r\nId,Prediction", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Prizes", "content": "
22001,1
22002,0
22003,0
22004,1
etc.
You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.
\r\n\r\n Privately sharing code or data outside of teams is not permitted.\r\n It's okay to share code if made available to all participants on the forums.\r\n
\r\nKaggle and the competition host have the right to publicly disseminate any entries or models.
\r\n\r\n Winning solutions need to be made available under\r\n a popular OSI-approved license\r\n in order to be eligible for recognition and prize money.\r\n
\r\n\r\n Prizes will be awarded after the winners have posted their solutions to the competition forum.\r\n Winners must post or link to their solutions within seven (7) days of being notified of their winning status.\r\n
\r\n\r\n Team mergers are allowed and can be performed by the team leader. In order to merge, the combined team must have a total submission count less than or equal to the maximum allowed as of the merge date. The maximum allowed is the number of submissions per day multiplied by the number of days the competition has been running.
\r\n
There is no maximum team size.
\r\nYou may submit a maximum of 5 entries per day.
\r\nYou may select up to 2 final submissions for judging.
\r\nStart Date: 4/21/2014 5:21 AM UTC
\r\nMerger Deadline: None
\r\nEntry Deadline: 7/20/2014 11:59 PM UTC
\r\nEnd Date: 7/27/2014 11:59 PM UTC
\r\n\t\r\nYou are not allowed to use data from the original study, except as provided on this competition's Data page.
\r\nAs a correction to the above rule, Winners must post or link to their solutions within seven (7) days of being notified of their winning status.
\r\nThe winning teams must submit a written description of their solution, of at least one page and consistent with this template, as additional material to the code. All participants are also invited to submit a written description of their approach through the public forum, or privately to decmeg2014@list.fbk.eu. The descriptions of the models will be used to summarize the results of the competition at the 19th International Conference on Biomagnetism (Biomag2014) and in later publications.
\r\nThe dataset of this competition is distributed under the Creative Commons license Attribution 3.0. The copyright holders are UK Medical Research Council, Richard Henson and Emanuele Olivetti.
\r\nAnd now a brief interlude from our lawyers:
\r\nCOMPETITION NAME (the 'Competition'): DecMeg2014 - Decoding the Human Brain
\r\nCOMPETITION SPONSOR: Fondazione Bruno Kessler
\r\nCOMPETITION WEBSITE: https://www.kaggle.com/c/decoding-the-human-brain
\r\nPRIZES: $5,000 among 3 prizes
\r\nWINNER LICENSE TYPE: Open Source license
\r\nMAXIMUM TEAM SIZE: as listed above
\r\nMAXIMUM SUBMISSIONS PER DAY: as listed above
\r\nThese are the complete, official rules for the Competition (the 'Competition Rules') and incorporate by reference the contents of the Competition Website listed above.
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\r\n'Submission' means the material submitted by you in the manner and format specified on the Website via the Submission form on the Website. You may submit up to the maximum number of Submissions per day as specified above. All Submissions must be uploaded to the Website in the manner and format specified on the Website. Submissions must be received prior to the Competition deadline and adhere to the guidelines for Submissions specified on the Website.
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\r\nA Submission will be ineligible to win a prize if it was developed using code containing or depending on software licensed under an open source license:
\r\n* other than an Open Source Initiative-approved license (see <http://opensource.org/>); or
* an open source license that prohibits commercial use.
This Competition is a challenge of skill and the final results are determined solely by leaderboard ranking on the private leaderboard (subject to compliance with these Competition Rules). Participants' scores and ranks on the Competition Website at any given stage of the Competition will be based on the evaluation metric described on the Competition Website, as determined by applying the predictions in the Submission to the ground truth of a validation dataset whose instances were a fixed set sampled from the Data.
\r\nThe evaluation metric used for scoring and ranking Submissions will be displayed on the Competition Website.
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\r\n* disqualify your Submission(s); or
* require that you remediate within one week all issues identified in your Submission(s) (including, without limitation, the resolution of license conflicts, the fulfillment of all obligations required by software licenses, and the removal of any software that violates the software restrictions).
A tie between two or more valid and identically ranked submissions will be resolved in favour of the tied submission that was submitted first.
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\r\nIf a potential winning Participant or Team member is a U.S. citizen, potential winner must also sign and return an IRS W-9 form, or if a foreign resident, an IRS W-8BEN form, within the stated time in order to claim the prize.
\r\nPotential winners will be disqualified and the prize may be awarded to an alternate winner (the next-ranked qualified Participant on the leaderboard) if
\r\n* the required documentation is not returned within 7 days after receipt of any request to provide documentation;
* prize notification letter/email or prize is returned as undeliverable; or
* potential winner or winning Team member is disqualified for any reason.
By accepting any Prize, each Participant receiving a Prize thereby agrees to use of his/her name, address, likeness and/or Prize information by Kaggle and Competition Sponsor for promotional purposes in any medium without additional compensation.
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\r\nIf the Winner License Type for the Competition (see Winner License Type above) is Open Source License, then each Winner by accepting a Prize thereby:
\r\n* licenses their winning Submission and the source code used to generate the Submission under the MIT License (an open source software license commonly described at <http://opensource.org/licenses/MIT>), unless another open source license is chosen explicitly from the list of those approved by the Open Source Initiative at <http://opensource.org/licenses/>; and
* represents that he/she/it has the unrestricted right to grant that license.
Participating using more than one Kaggle account is deemed cheating and, if discovered, will result in disqualification from the Competition and any other affected Competitions and may result in banning or deactivation of affected Kaggle accounts.
\r\nAfter verification of eligibility, each Prize winner will receive the prize in the form of a check or wire transfer made out to the Prize winner (if an individual, or to the individual Team members if a Team). Allow 30 days from final confirmation for Prize delivery. Any winners who are U.S. citizens will receive an IRS 1099 form in the amount of their prize at the appropriate time. Prize winners are responsible for any taxes, fees or other liability resulting from their receipt of a Prize.
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\r\nIf a Team wins a monetary Prize, Competition Sponsor will allocate the Prize money in even shares between the Team members unless the Team unanimously contacts Kaggle via the Competition Website within three business days following the Submission deadline to request an alternative prize distribution.
\r\nBy registering, you agree that (a) your Account is complete, correct and accurate and (b) your registration may be rejected or terminated and all Entries submitted by you and/or your Team may be disqualified if any of the information in your Account is (or Competition Sponsor has reasonable grounds to believe it is) incomplete, incorrect or inaccurate. You are solely responsible for your Account. All registration information is deemed collected in the United States.
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\r\n* is your own original work, or is used by permission, in which case full and proper credit and identify is given and the third party contributions are clearly identified within your Submission;
* does not contain confidential information or trade secrets and is not the subject of a registered patent or pending patent application;
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* does not and will not violate any applicable law, statute, ordinance, rule or regulation;
* does not trigger any reporting or royalty obligation to any third party; and
* was not previously published and has not won any other prize/award.
A breach of any of these warranties will result in the corresponding Submission being invalid.
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", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Timeline", "content": "All deadlines are at 11:59 PM UTC on the corresponding day unless otherwise noted. The organizers reserve the right to update the contest timeline as the contest progresses.
", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Winners", "content": "First Place:
\r\nSecond Place:
\r\nThird Place:
\r\n