iMap4: An open source toolbox for the statistical fixation mapping of eye movement data with linear mixed modeling

[1]  JAMES SUROWIECKI,et al.  The wisdom of crowds , 2016, The Lancet.

[2]  Junpeng Lao,et al.  Mapping female bodily features of attractiveness , 2016, Scientific Reports.

[3]  Olivier Renaud,et al.  A general permutation approach for analyzing repeated measures ANOVA and mixed-model designs , 2015 .

[4]  Nicolas Chopin,et al.  The Poisson transform for unnormalised statistical models , 2014, Stat. Comput..

[5]  Stephen M. Smith,et al.  Permutation inference for the general linear model , 2014, NeuroImage.

[6]  Junpeng Lao,et al.  An Appropriate Use of IMap Produces Correct Statistical Results: A Reply to McManus (2013) “IMap and IMap2 Produce Erroneous Statistical Maps of Eye-Movement Differences” , 2014, Perception.

[7]  Alberto D. Pascual-Montano,et al.  A survey of dimensionality reduction techniques , 2014, ArXiv.

[8]  Syed Omer Gilani,et al.  Parallel programming of saccades during natural scene viewing: evidence from eye movement positions. , 2013, Journal of vision.

[9]  Simon Barthelmé,et al.  Modeling fixation locations using spatial point processes. , 2012, Journal of vision.

[10]  Diogo M. Camacho,et al.  Wisdom of crowds for robust gene network inference , 2012, Nature Methods.

[11]  S. Liversedge,et al.  Oxford handbook of eye movements , 2011 .

[12]  Vince D. Calhoun,et al.  EEGIFT: Group Independent Component Analysis for Event-Related EEG Data , 2011, Comput. Intell. Neurosci..

[13]  Sébastien Miellet,et al.  iMap: a novel method for statistical fixation mapping of eye movement data , 2011, Behavior research methods.

[14]  Guillaume A. Rousselet,et al.  LIMO EEG: A Toolbox for Hierarchical LInear MOdeling of ElectroEncephaloGraphic Data , 2011, Comput. Intell. Neurosci..

[15]  Robert Oostenveld,et al.  FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data , 2010, Comput. Intell. Neurosci..

[16]  R. Caldara,et al.  When East meets West: gaze-contingent Blindspots abolish cultural diversity in eye movements for faces , 2010 .

[17]  Sara Kherad-Pajouh,et al.  An exact permutation method for testing any effect in balanced and unbalanced fixed effect ANOVA , 2010, Comput. Stat. Data Anal..

[18]  R. Caldara,et al.  Putting Culture Under the ‘Spotlight’ Reveals Universal Information Use for Face Recognition , 2010, PloS one.

[19]  Mollie E. Brooks,et al.  Generalized linear mixed models: a practical guide for ecology and evolution. , 2009, Trends in ecology & evolution.

[20]  Stephen M. Smith,et al.  Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference , 2009, NeuroImage.

[21]  R. Baayen,et al.  Mixed-effects modeling with crossed random effects for subjects and items , 2008 .

[22]  Rachael E. Jack,et al.  Culture Shapes How We Look at Faces , 2008, PloS one.

[23]  Karl J. Friston,et al.  Mixed-effects and fMRI studies , 2005, NeuroImage.

[24]  Mikhail Belkin,et al.  Laplacian Eigenmaps for Dimensionality Reduction and Data Representation , 2003, Neural Computation.

[25]  Felix Famoye,et al.  Plane Answers to Complex Questions: Theory of Linear Models , 2003, Technometrics.

[26]  Mark Von Tress,et al.  Generalized, Linear, and Mixed Models , 2003, Technometrics.

[27]  Andrew T Duchowski,et al.  A breadth-first survey of eye-tracking applications , 2002, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[28]  Vincent J. Carey,et al.  Mixed-Effects Models in S and S-Plus , 2001 .

[29]  D. Bates,et al.  Mixed-Effects Models in S and S-PLUS , 2001 .

[30]  K. Rayner.  Eye movements in reading and information processing: 20 years of research. , 1998, Psychological bulletin.

[31]  R. Christensen.  Plane Answers to Complex Questions: The Theory of Linear Models. , 1997 .

[32]  S. Raudenbush,et al.  Hierarchical Linear Models: Applications and Data Analysis Methods , 1992 .

[33]  H. Pollard.  The Poisson transform , 1955 .

[34]  Andrea Bergmann,et al.  Statistical Parametric Mapping The Analysis Of Functional Brain Images , 2016 .

[35]  Erik D. Reichle,et al.  Eye movements in reading and information processing : , 2015 .

[36]  Karl J. Friston,et al.  Statistical parametric mapping , 2013 .

[37]  M. Tribus,et al.  Probability theory: the logic of science , 2005 .

[38]  David A. Forsyth,et al.  Shape, Contour and Grouping in Computer Vision , 1999, Lecture Notes in Computer Science.

[39]  Yoshua Bengio,et al.  Object Recognition with Gradient-Based Learning , 1999, Shape, Contour and Grouping in Computer Vision.

[40]  Thomas E. Nichols,et al.  Cluster-based computational methods for mass univariate analyses of event-related brain potentials/fields: A simulation study , 2015, Journal of Neuroscience Methods.

[41]  M. Masson,et al.  Please Scroll down for Article Visual Cognition a Linear Mixed Model Analysis of Masked Repetition Priming , 2022 .

[42]  W. Einhäuser,et al.  Annals of the New York Academy of Sciences Issue: Competitive Visual Processing across Space and Time a New Approach to Modeling the Influence of Image Features on Fixation Selection in Scenes , 2022 .