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Information-optimal local features automatically attract covert and overt attention

<p><strong>COVERT ATTENTION FOLDER&nbsp;</strong></p> <p>The&nbsp;<strong>&quot;COVERT ATTENTION&quot; folder</strong>&nbsp;contains&nbsp;<strong>one hundred .mat files</strong>&nbsp;(eight&nbsp;files for sixteen participants).&nbsp;</p> <p>The file name for each subject (from S01 to S16) describes:</p> <ul> <li>Condition: Experimental or Control</li> <li>Cue Validity: 50% or 80%</li> <li>Type of trials: Neutral or Non-Neutral</li> </ul> <p>Each matrix of Neutral trials and Non-Neutral Control trials contains 8 columns:</p> <ul> <li>trial number</li> <li>side of presentation of the gabor: 1=SX; 2=DX&nbsp;</li> <li>gabor orientation: 1 = -20&deg;; 2 = +20&deg;</li> <li>gabor contrast</li> <li>subject&#39;s response: 1 = -20&deg;; 2 = +20&deg;</li> <li>correct response: 1= right; 0=wrong</li> <li>trial type: 1= Valid trial; 2 = Invalid trial</li> <li>Reaction time</li> </ul> <p>Each matrix of Non-Neutral Experimental trials contains 10 columns:</p> <ul> <li>trial number</li> <li>side of presentation of the gabor: 1=SX; 2=DX&nbsp;</li> <li>gabor orientation: 1 = -20&deg;; 2 = +20&deg;</li> <li>gabor contrast</li> <li>subject&#39;s response: 1 = -20&deg;; 2 = +20&deg;</li> <li>correct response: 1= right; 0=wrong</li> <li>trial type: 1= Valid trial; 2 = Invalid trial</li> <li>Identification code of the specific&nbsp;<em>optimal feature</em>&nbsp;presented</li> <li>Identification code of the specific&nbsp;<em>non-optimal</em>&nbsp;feature presented</li> <li>Reaction time</li> </ul> <p>&nbsp;</p> <p><strong>OVERT ATTENTION FOLDER</strong></p> <p>The file name for each subject (from S01 to S16) describes:</p> <ul> <li>Condition: Experimental or Control</li> <li>Cue Validity: 50% or 80%</li> </ul> <p>The&nbsp;<strong>&quot;OVERT ATTENTION&quot; folder</strong>&nbsp;contains&nbsp;<strong>sixty-four .EDF files</strong>&nbsp;(four&nbsp;files for sixteen participants).&nbsp;The&nbsp;EyeLink EDF* files&nbsp;contain many types of data, including eye movement events (BLINKS, FIXATIONS, SACCADES), messages (including the &ldquo;default&rdquo; ones by Eyelink, and the custom made ones, defining the single trial&rsquo;s specific properties: this type of messages starts with &ldquo;Trialinfo&rdquo;), button presses, and eye-data samples.&nbsp;&nbsp;Here we have used the (calibrated) x and y position data of the right eye.&nbsp;Custom-made matlab scripts (available upon request to the authors) have been used to parse the data into trials, filter eye position and estimate eye velocity, select exploitable trials, detect and analyze saccades, etc.&nbsp;The&nbsp;EDF file&nbsp;format is a highly compressed binary format, intended for use with SR Research&nbsp;EyeLink&nbsp;viewers and applications. EDF files are not readable, they need to be transformed into a readable format (typically ASCII). A tool to transform edf files into ascii is freely available on the SR Research Support online forum site:&nbsp;https://download.sr-support.com/dispdoc/page25.html.</p> <p>The folder also contains&nbsp;<strong>sixty-four .mat files</strong>&nbsp;(four&nbsp;files for sixteen participants), containing&nbsp;the relevant information of each trial.</p> <p>Each matrix of the Control condition contains 5 columns:</p> <ul> <li>trial number</li> <li>side of presentation of the place holder: 1=SX; 2=DX&nbsp;</li> <li>Type of trial: 0 = Neutral, 1 = Valid, 2 = Invalid</li> <li>Saccade to target: 1 correct saccade 0 no saccade</li> <li>Saccade latency</li> </ul> <p>Each matrix of Experimental condition contains 8 columns:</p> <ul> <li>trial number</li> <li>side of presentation of the place holder: 1=SX; 2=DX&nbsp;</li> <li>Identification code of the specific&nbsp;<em>optimal feature</em>&nbsp;presented</li> <li>Identification code of the specific&nbsp;<em>non-optimal</em>&nbsp;feature presented</li> <li>Type of trial: 3 = neutral, 4 = valid, 5 = invalid</li> <li>Saccade to target: 1 correct saccade 0 no saccade</li> <li>Saccade latency</li> </ul>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4

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