Reproducibility of brain‐cognition relationships using three cortical surface‐based protocols: An exhaustive analysis based on cortical thickness
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Manuel Desco | Joost Janssen | Shantanu H. Joshi | Anand A Joshi | Eugenio Marinetto | Paul M Thompson | Anand A. Joshi | Kenia Martínez | Roberto Colom | Julio Villalon-Reina | Miguel Burgaleta | Sherif Karama | Sarah K Madsen | Francisco J Román | P. Thompson | M. Desco | S. Karama | J. Villalon-Reina | S. Madsen | R. Colom | J. Janssen | F. J. Román | K. Martínez | M. Burgaleta | E. Marinetto | Shantanu H Joshi | P. Thompson | P. Thompson | P. Thompson
[1] Jacob Cohen. Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.
[2] Alan C Evans,et al. Impact of scale space search on age‐ and gender‐related changes in MRI‐based cortical morphometry , 2013, Human brain mapping.
[3] Kenia Martínez,et al. Improvement in working memory is not related to increased intelligence scores , 2010 .
[4] Alan C. Evans,et al. Enhancement of MR Images Using Registration for Signal Averaging , 1998, Journal of Computer Assisted Tomography.
[5] Arthur W. Toga,et al. Diffeomorphic Sulcal Shape Analysis on the Cortex , 2012, IEEE Transactions on Medical Imaging.
[6] K. Worsley,et al. Unified univariate and multivariate random field theory , 2004, NeuroImage.
[7] Alan C. Evans,et al. A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.
[8] Alan C. Evans,et al. Multiple surface identification and matching in magnetic resonance images , 1994, Other Conferences.
[9] V. Gil,et al. Medición en ciencias sociales y de la salud , 2011 .
[10] Thomas E. Nichols,et al. Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate , 2002, NeuroImage.
[11] Roberto Colom,et al. General intelligence and memory span: Evidence for a common neuroanatomic framework , 2007, Cognitive neuropsychology.
[12] B. Thompson,et al. EFFECTS OF SAMPLE SIZE, ESTIMATION METHODS, AND MODEL SPECIFICATION ON STRUCTURAL EQUATION MODELING FIT INDEXES , 1999 .
[13] G. Sapiro,et al. Geometric partial differential equations and image analysis [Book Reviews] , 2001, IEEE Transactions on Medical Imaging.
[14] Alan C. Evans,et al. Automated 3-D Extraction of Inner and Outer Surfaces of Cerebral Cortex from MRI , 2000, NeuroImage.
[15] Cheuk Y. Tang,et al. Gray Matter and Intelligence Factors: Is There a Neuro-g?. , 2009 .
[16] B. Byrne. Structural Equation Modeling with LISREL, PRELIS, and SIMPLIS: Basic Concepts, Applications, and Programming , 1998 .
[17] R. Leahy,et al. Magnetic Resonance Image Tissue Classification Using a Partial Volume Model , 2001, NeuroImage.
[18] P. Bentler,et al. Comparative fit indexes in structural models. , 1990, Psychological bulletin.
[19] Thomas J. Bouchard,et al. The structure of human intelligence: It is verbal, perceptual, and image rotation (VPR), not fluid and crystallized , 2005 .
[20] Alan C. Evans,et al. Fast and robust parameter estimation for statistical partial volume models in brain MRI , 2004, NeuroImage.
[21] Lorena R. R. Gianotti,et al. Functional brain network efficiency predicts intelligence , 2012, Human brain mapping.
[22] R. Haier,et al. The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence , 2007, Behavioral and Brain Sciences.
[23] Richard L. Lewis,et al. The mind and brain of short-term memory. , 2008, Annual review of psychology.
[24] M. A. Anusuya,et al. Human Intelligence , 1965, Nature.
[25] A. Dale,et al. Distinct genetic influences on cortical surface area and cortical thickness. , 2009, Cerebral cortex.
[26] Alan C. Evans,et al. Measurement of Cortical Thickness Using an Automated 3-D Algorithm: A Validation Study , 2001, NeuroImage.
[27] R. Haier,et al. Reversed hierarchy in the brain for general and specific cognitive abilities: A morphometric analysis , 2014, Human brain mapping.
[28] Stephen M Smith,et al. Fast robust automated brain extraction , 2002, Human brain mapping.
[29] Suzanne E. Welcome,et al. Longitudinal Mapping of Cortical Thickness and Brain Growth in Normal Children , 2022 .
[30] Michael C. Pyryt. Human cognitive abilities: A survey of factor analytic studies , 1998 .
[31] K. McGrew. CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research , 2009 .
[32] D. V. Essen,et al. Cognitive neuroscience 2.0: building a cumulative science of human brain function , 2010, Trends in Cognitive Sciences.
[33] Alan C. Evans,et al. BigBrain: An Ultrahigh-Resolution 3D Human Brain Model , 2013, Science.
[34] John B. Carroll,et al. The Higher-stratum Structure of Cognitive Abilities: Current Evidence Supports g and About Ten Broad Factors , 2003 .
[35] A. Toga,et al. Mapping sulcal pattern asymmetry and local cortical surface gray matter distribution in vivo: maturation in perisylvian cortices. , 2002, Cerebral cortex.
[36] Steven Robbins,et al. An unbiased iterative group registration template for cortical surface analysis , 2007, NeuroImage.
[37] P. Bentler,et al. Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .
[38] J. S. Long,et al. Testing Structural Equation Models , 1993 .
[39] R. Haier,et al. Human intelligence and brain networks , 2010, Dialogues in clinical neuroscience.
[40] Alan C. Evans,et al. Cortical thickness analysis examined through power analysis and a population simulation , 2005, NeuroImage.
[41] D. Collins,et al. Automatic 3D Intersubject Registration of MR Volumetric Data in Standardized Talairach Space , 1994, Journal of computer assisted tomography.
[42] Rex E. Jung,et al. Gray matter correlates of fluid, crystallized, and spatial intelligence: Testing the P-FIT model , 2009 .
[43] Michael W. Cole,et al. Global Connectivity of Prefrontal Cortex Predicts Cognitive Control and Intelligence , 2012, The Journal of Neuroscience.
[44] Rainer Goebel,et al. Measuring structural–functional correspondence: Spatial variability of specialised brain regions after macro-anatomical alignment , 2012, NeuroImage.
[45] Brian A. Nosek,et al. Power failure: why small sample size undermines the reliability of neuroscience , 2013, Nature Reviews Neuroscience.
[46] Richard J. Haier,et al. Neuroanatomic overlap between intelligence and cognitive factors: Morphometry methods provide support for the key role of the frontal lobes , 2013, NeuroImage.
[47] M. Fox,et al. Individual Variability in Functional Connectivity Architecture of the Human Brain , 2013, Neuron.
[48] J. Raven,et al. Manual for Raven's progressive matrices and vocabulary scales , 1962 .
[49] Alan C. Evans,et al. Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification , 2005, NeuroImage.
[50] Gil Gaudia. Intelligence about Intelligence , 1973, The Elementary School Journal.
[51] Rex E. Jung,et al. Cortical thickness correlates of specific cognitive performance accounted for by the general factor of intelligence in healthy children aged 6 to 18 , 2011, NeuroImage.
[52] Richard M. Leahy,et al. A Method for Automated Cortical Surface Registration and Labeling , 2012, WBIR.
[53] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[54] C. Adcock,et al. Primary Mental Abilities. , 1971, The Journal of general psychology.
[55] L. Nyberg,et al. Common fronto-parietal activity in attention, memory, and consciousness: Shared demands on integration? , 2005, Consciousness and Cognition.
[56] I. Deary. 125 years of intelligence in the American Journal of Psychology. , 2012, The American journal of psychology.
[57] Kiralee M. Hayashi,et al. Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia , 2004, NeuroImage.
[58] Psychometric monographs , 1952 .
[59] Richard M. Leahy,et al. Geodesic curvature flow on surfaces for automatic sulcal delineation , 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).
[60] Alan C. Evans,et al. Automatic "pipeline" analysis of 3-D MRI data for clinical trials: application to multiple sclerosis , 2002, IEEE Transactions on Medical Imaging.
[61] Anderson M. Winkler,et al. Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies , 2010, NeuroImage.
[62] P. Ackerman,et al. Individual differences in working memory within a nomological network of cognitive and perceptual speed abilities. , 2002, Journal of experimental psychology. General.
[63] Russell A. Poldrack,et al. Large-scale automated synthesis of human functional neuroimaging data , 2011, Nature Methods.
[64] J Mazziotta,et al. A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[65] R. Cabeza,et al. Imaging Cognition II: An Empirical Review of 275 PET and fMRI Studies , 2000, Journal of Cognitive Neuroscience.
[66] Arthur W. Toga,et al. A Probabilistic Atlas of the Human Brain: Theory and Rationale for Its Development The International Consortium for Brain Mapping (ICBM) , 1995, NeuroImage.
[67] Jason Lerch,et al. Measuring Cortical Thickness , 2001 .
[68] J. Flynn,et al. Intelligence: new findings and theoretical developments. , 2012, The American psychologist.
[69] T. Yarkoni. Big Correlations in Little Studies: Inflated fMRI Correlations Reflect Low Statistical Power—Commentary on Vul et al. (2009) , 2009, Perspectives on psychological science : a journal of the Association for Psychological Science.
[70] R. Colom,et al. Working memory and intelligence are highly related constructs, but why? , 2008 .
[71] Alan C. Evans,et al. Depth potential function for folding pattern representation, registration and analysis , 2009, Medical Image Anal..
[72] Alan C. Evans,et al. A method for identifying geometrically simple surfaces from three-dimensional images , 1998 .