Each row represents a complete analysis for a single subject. Columns represent different levels of the context dimension (spatial position) held fixed during training and the dotted line represents chance performance. Group descriptive statistics (mean and standard errors) are presented in the bottom row. Also shown are results of significant cross-classification and classification accuracy invariance (pairwise comparisons) tests.</p
<p>The mean orientation-discrimination performance (<i>d</i>') was plotted for each condition as a f...
This file contains accuracy metrics for each classification approach x input type combination examin...
<p>(a) An axial slice of a brain in the standard Talairach space showing a section through the two 1...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...
<p>(A) Classification accuracy when the number of averaged trials was different. Each colored line r...
<p>Mean response times (A) and percentage of errors (B) in the orientation detection task as a funct...
<p>Decoding accuracy (proportion correct) obtained for the 100 most discriminative voxels is plotted...
<p>The table shows the cross-validation performance of our method on the labeled data points. The me...
<p>A. Classification model fot target detection built from the Color Luminance experiment and used t...
<p>The binary classification accuracy, estimated with cross validation is plotted for each condition...
<p>Summary of the labeling accuracy obtained for the training set, for all the discrimination proble...
(A) Object detection task. Left column: full code (red) optimized for image reconstruction; right co...
<p>(A) Localization accuracy across subjects for each direction. Each circle represents the percenta...
<p>(A) Performance for groups of trials that differ in how far off the cued direction the test direc...
<p>The mean orientation-discrimination performance (<i>d</i>') was plotted for each condition as a f...
This file contains accuracy metrics for each classification approach x input type combination examin...
<p>(a) An axial slice of a brain in the standard Talairach space showing a section through the two 1...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...
<p>(A) Classification accuracy when the number of averaged trials was different. Each colored line r...
<p>Mean response times (A) and percentage of errors (B) in the orientation detection task as a funct...
<p>Decoding accuracy (proportion correct) obtained for the 100 most discriminative voxels is plotted...
<p>The table shows the cross-validation performance of our method on the labeled data points. The me...
<p>A. Classification model fot target detection built from the Color Luminance experiment and used t...
<p>The binary classification accuracy, estimated with cross validation is plotted for each condition...
<p>Summary of the labeling accuracy obtained for the training set, for all the discrimination proble...
(A) Object detection task. Left column: full code (red) optimized for image reconstruction; right co...
<p>(A) Localization accuracy across subjects for each direction. Each circle represents the percenta...
<p>(A) Performance for groups of trials that differ in how far off the cued direction the test direc...
<p>The mean orientation-discrimination performance (<i>d</i>') was plotted for each condition as a f...
This file contains accuracy metrics for each classification approach x input type combination examin...
<p>(a) An axial slice of a brain in the standard Talairach space showing a section through the two 1...