Stimulus-specific random effects inflate false-positive classification accuracy in multivariate-voxel-pattern-analysis: A solution with generalized mixed-effects modelling

[1]  Xiangmin Xu,et al.  Beyond t test and ANOVA: applications of mixed-effects models for more rigorous statistical analysis in neuroscience research , 2021, Neuron.

[2]  K. Murayama,et al.  Unnecessary reliance on multilevel modelling to analyse nested data in neuroscience: When a traditional summary-statistics approach suffices , 2021, Current research in neurobiology.

[3]  Matthew D. Lieberman,et al.  Tools of the Trade Multivoxel pattern analysis in fMRI: a practical introduction for social and affective neuroscientists , 2020, Social cognitive and affective neuroscience.

[4]  Jingyuan Ren,et al.  The function of the hippocampus and middle temporal gyrus in forming new associations and concepts during the processing of novelty and usefulness features in creative designs , 2020, NeuroImage.

[5]  Qi Wang,et al.  Inter-subject pattern analysis: A straightforward and powerful scheme for group-level MVPA , 2019, NeuroImage.

[6]  C. Feng,et al.  The p-value and model specification in statistics , 2019, General Psychiatry.

[7]  Geoff Cumming,et al.  Estimation for Better Inference in Neuroscience , 2019, eNeuro.

[8]  M. Kawato,et al.  Multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates , 2019, bioRxiv.

[9]  D. Wagner,et al.  The neural representation of self is recapitulated in the brains of friends: A round-robin fMRI study. , 2018, Journal of personality and social psychology.

[10]  K. Murayama,et al.  Time-specific Errors in Growth Curve Modeling: Type-1 Error Inflation and a Possible Solution with Mixed-Effects Models , 2018, Multivariate behavioral research.

[11]  R. Saxe,et al.  Cortical responses to dynamic emotional facial expressions generalize across stimuli, and are sensitive to task-relevance, in adults with and without Autism , 2018, Cortex.

[12]  Massimo Silvetti,et al.  Human midcingulate cortex encodes distributed representations of task progress , 2018, Proceedings of the National Academy of Sciences.

[13]  H. Steven Scholte,et al.  How to control for confounds in decoding analyses of neuroimaging data , 2018, NeuroImage.

[14]  Markus Brauer,et al.  Linear Mixed-Effects Models and the Analysis of Nonindependent Data: A Unified Framework to Analyze Categorical and Continuous Independent Variables that Vary Within-Subjects and/or Within-Items , 2017, Psychological methods.

[15]  Daniel M. McNeish Small Sample Methods for Multilevel Modeling: A Colloquial Elucidation of REML and the Kenward-Roger Correction , 2017, Multivariate behavioral research.

[16]  Oluwasanmi Koyejo,et al.  What's in a pattern? Examining the type of signal multivariate analysis uncovers at the group level , 2016, NeuroImage.

[17]  Thomas E. Nichols,et al.  Fixing the stimulus-as-fixed-effect fallacy in task fMRI , 2016, bioRxiv.

[18]  Rosemary A. Cowell,et al.  Distributed category‐specific recognition‐memory signals in human perirhinal cortex , 2016, Hippocampus.

[19]  J. Haynes A Primer on Pattern-Based Approaches to fMRI: Principles, Pitfalls, and Perspectives , 2015, Neuron.

[20]  Ethan Kross,et al.  Discriminating Neural Representations of Physical and Social Pains: How Multivariate Statistics Challenge the 'shared Representation' Theory of Pain Rogachov a Hanna Jr, and Wager Td. Separate Neural Representations for Physical Pain and Social Rejection , 2022 .

[21]  Veronica X. Yan,et al.  Type-1 error inflation in the traditional by- participant analysis to metamemory accuracy: a generalized mixed-effects model perspective , 2017 .

[22]  Jonathan D. Cohen,et al.  Confounds in multivariate pattern analysis: Theory and rule representation case study , 2013, NeuroImage.

[23]  A. Caramazza,et al.  Brain Regions That Represent Amodal Conceptual Knowledge , 2013, The Journal of Neuroscience.

[24]  D. Barr,et al.  Random effects structure for confirmatory hypothesis testing: Keep it maximal. , 2013, Journal of memory and language.

[25]  Yi Chen,et al.  Statistical inference and multiple testing correction in classification-based multi-voxel pattern analysis (MVPA): Random permutations and cluster size control , 2011, NeuroImage.

[26]  D. A. Kenny,et al.  Treating stimuli as a random factor in social psychology: a new and comprehensive solution to a pervasive but largely ignored problem. , 2012, Journal of personality and social psychology.

[27]  M. Peelen,et al.  Supramodal Representations of Perceived Emotions in the Human Brain , 2010, The Journal of Neuroscience.

[28]  Kenneth A. Norman,et al.  Recollection, Familiarity, and Cortical Reinstatement: A Multivoxel Pattern Analysis , 2009, Neuron.

[29]  F. Tong,et al.  Decoding reveals the contents of visual working memory in early visual areas , 2009, Nature.

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

[31]  Sharon L. Thompson-Schill,et al.  Item analysis in functional magnetic resonance imaging , 2007, NeuroImage.

[32]  Rainer Goebel,et al.  Information-based functional brain mapping. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[33]  F. Tong,et al.  Decoding the visual and subjective contents of the human brain , 2005, Nature Neuroscience.

[34]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[35]  A. Ishai,et al.  Distributed and Overlapping Representations of Faces and Objects in Ventral Temporal Cortex , 2001, Science.

[36]  D. A. Kenny,et al.  Consequences of violating the independence assumption in analysis of variance. , 1986 .

[37]  Thomas D. Wickens,et al.  On the choice of design and of test statistic in the analysis of experiments with sampled materials , 1983 .

[38]  H. H. Clark The language-as-fixed-effect fallacy: A critique of language statistics in psychological research. , 1973 .