Classification of autistic individuals and controls using cross-task characterization of fMRI activity

NeuroImage: Clinical - Tập 10 - Trang 78-88 - 2016
Guillaume Chanel1, Swann Pichon1, Laurence Conty2, Sylvie Berthoz3,4, Coralie Chevallier5, Julie Grèzes6,7,5
1Université de Genève = University of Geneva
2Laboratoire de Psychopathologie et Neuropsychologie
3Centre de recherche en épidémiologie et santé des populations
4Institut Mutualiste de Montsouris
5Laboratoire de Neurosciences Cognitives & Computationnelles
6Center for NeuroImaging Research-Human MRI Neuroimaging core facility for clinical research [ICM Paris]
7Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute

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Tài liệu tham khảo

Allison, 2000, Social perception from visual cues: role of the STS region, Trends Cogn. Sci., 4, 267, 10.1016/S1364-6613(00)01501-1

American Psychiatric Association, 2000

Anderson, 2011, Functional connectivity magnetic resonance imaging classification of autism, Brain, 134, 3742, 10.1093/brain/awr263

Baron-Cohen, 2001, The autism-spectrum quotient (AQ): evidence from Asperger syndrome/high-functioning autism, males and females, scientists and mathematicians, J. Autism Dev. Disord., 31, 5, 10.1023/A:1005653411471

Bishop, 2006

Bishop, 2007, Neurocognitive mechanisms of anxiety: an integrative account, Trends Cogn. Sci., 11, 307, 10.1016/j.tics.2007.05.008

Breitling, 2004, Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments, FEBS Lett., 573, 83, 10.1016/j.febslet.2004.07.055

Castelli, 2000, Movement and mind: a functional imaging study of perception and interpretation of complex intentional movement patterns, Neuroimage, 12, 314, 10.1006/nimg.2000.0612

Castelli, 2002, Autism, Asperger syndrome and brain mechanisms for the attribution of mental states to animated shapes, Brain, 125, 1839, 10.1093/brain/awf189

Chevallier, 2012, Brief report: selective social anhedonia in high functioning autism, J. Autism Dev. Disord., 42, 1504, 10.1007/s10803-011-1364-0

Chevallier, 2012, The social motivation theory of autism, Trends Cogn. Sci., 16, 231, 10.1016/j.tics.2012.02.007

Conty, 2012

Coutanche, 2011, Multi-voxel pattern analysis of fMRI data predicts clinical symptom severity, Neuroimage, 57, 113, 10.1016/j.neuroimage.2011.04.016

Deen, 2012, Perspective: brain scans need a rethink, Nature, 491, S20, 10.1038/491S20a

Deshpande, 2013, Identification of neural connectivity signatures of autism using machine learning, Front. Hum. Neurosci., 7, 670, 10.3389/fnhum.2013.00670

Dichter, 2012, Functional magnetic resonance imaging of autism spectrum disorders, Dialogues Clin. Neurosci., 14, 319, 10.31887/DCNS.2012.14.3/gdichter

Eckblad, 1982

Ecker, 2014, Neuroimaging in autism—from basic science to translational research, Nat. Rev. Neurol., 10, 82, 10.1038/nrneurol.2013.276

Eickhoff, 2005, A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data, Neuroimage, 25, 1325, 10.1016/j.neuroimage.2004.12.034

Eisinga, 2013, The exact probability distribution of the rank product statistics for replicated experiments, FEBS Lett., 587, 677, 10.1016/j.febslet.2013.01.037

Friston, 1996, Movement-related effects in fMRI time-series, Magn. Reson. Med., 35, 346, 10.1002/mrm.1910350312

Fu, 2008, Pattern classification of sad facial processing: toward the development of neurobiological markers in depression, Biol. Psychiatry, 63, 656, 10.1016/j.biopsych.2007.08.020

Giese, 2003, Neural mechanisms for the recognition of biological movements, Nat. Rev. Neurosci., 4, 179, 10.1038/nrn1057

Goldani, 2014, Biomarkers in autism, Front. Psychiatry, 5, 100, 10.3389/fpsyt.2014.00100

Grèzes, 2007, Perceiving fear in dynamic body expressions, Neuroimage, 35, 959, 10.1016/j.neuroimage.2006.11.030

Guyon, 2002, Gene selection for cancer classification using support vector machines, Mach. Learn., 46, 389, 10.1023/A:1012487302797

Haxby, 2001, Distributed and overlapping representations of faces and objects in ventral temporal cortex, Science, 293, 2425, 10.1126/science.1063736

Haxby, 2014, Decoding neural representational spaces using multivariate pattern analysis, Annu. Rev. Neurosci., 37, 435, 10.1146/annurev-neuro-062012-170325

Iidaka, 2014, Resting state functional magnetic resonance imaging and neural network classified autism and control, Cortex, 63C, 55

Kanwisher, 1997, The fusiform face area: a module in human extrastriate cortex specialized for face perception, J. Neurosci., 17, 4302, 10.1523/JNEUROSCI.17-11-04302.1997

Kennedy, 2006, Failing to deactivate: resting functional abnormalities in autism, Proc. Natl. Acad. Sci. U. S. A., 103, 8275, 10.1073/pnas.0600674103

Kerns, 2015, Not to be overshadowed or overlooked: functional impairments associated with comorbid anxiety disorders in youth with ASD, Behav. Ther., 46, 29, 10.1016/j.beth.2014.03.005

Kosmadakis, 1995, Translation and validation of the Revised Social Anhedonia Scale. Study of the internal and concurrent validity in 126 normal subjects, Encéphale, 21, 437

Koziol, 2010, Comments on the rank product method for analyzing replicated experiments, FEBS Lett., 584, 941, 10.1016/j.febslet.2010.01.031

Kriegeskorte, 2006, Information-based functional brain mapping, Proc. Natl. Acad. Sci. U. S. A., 103, 3863, 10.1073/pnas.0600244103

Laconte, 2005, Support vector machines for temporal classification of block design fMRI data, NeuroImage, 26, 317, 10.1016/j.neuroimage.2005.01.048

London, 2014, Categorical diagnosis: a fatal flaw for autism research?, Trends Neurosci., 37, 683, 10.1016/j.tins.2014.10.003

Lord, 2000, The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism, J. Autism Dev. Disord., 30, 205, 10.1023/A:1005592401947

Mourão-Miranda, 2005, Classifying brain states and determining the discriminating activation patterns: Support Vector Machine on functional MRI data, Neuroimage, 28, 980, 10.1016/j.neuroimage.2005.06.070

Murdaugh, 2012, Differential deactivation during mentalizing and classification of autism based on default mode network connectivity, PLoS One, 7, e50064, 10.1371/journal.pone.0050064

Nettle, 2012, The evolutionary origins of mood and its disorders, Curr. Biol., 22, R712, 10.1016/j.cub.2012.06.020

Nichols, 2001, Nonparametric Permutation Tests For Functional Neuroimaging: A Primer with Examples, 25, 1

Noirhomme, 2014, Biased binomial assessment of cross-validated estimation of classification accuracies illustrated in diagnosis predictions, NeuroImage Clin., 4, 687, 10.1016/j.nicl.2014.04.004

Pelphrey, 2004, Neuroanatomical substrates of social cognition dysfunction in autism, Ment. Retard. Dev. Disabil. Res. Rev., 10, 259, 10.1002/mrdd.20040

Pereira, 2009, Machine learning classifiers and fMRI: a tutorial overview, Neuroimage, 45, S199, 10.1016/j.neuroimage.2008.11.007

Pichon, 2008, Emotional modulation of visual and motor areas by dynamic body expressions of anger, Soc. Neurosci., 3, 199, 10.1080/17470910701394368

Pichon, 2009, Two different faces of threat. Comparing the neural systems for recognizing fear and anger in dynamic body expressions, Neuroimage, 47, 1873, 10.1016/j.neuroimage.2009.03.084

Pichon, 2012, Threat prompts defensive brain responses independently of attentional control, Cereb. Cortex, 22, 274, 10.1093/cercor/bhr060

Pichon, 2015, Cumulative activation during positive and negative events and state anxiety predicts subsequent inertia of amygdala reactivity, Soc. Cogn. Affect. Neurosci., 10, 180, 10.1093/scan/nsu044

Pierce, 2004, The brain response to personally familiar faces in autism: findings of fusiform activity and beyond, Brain, 127, 2703, 10.1093/brain/awh289

Pitcher, 2014, Facial expression recognition takes longer in the posterior superior temporal sulcus than in the occipital face area, J. Neurosci., 34, 9173, 10.1523/JNEUROSCI.5038-13.2014

Power, 2012, Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion, Neuroimage, 59, 2142, 10.1016/j.neuroimage.2011.10.018

Power, 2014, Methods to detect, characterize, and remove motion artifact in resting state fMRI, Neuroimage, 84, 320, 10.1016/j.neuroimage.2013.08.048

Puce, 1996, Differential sensitivity of human visual cortex to faces, letterstrings, and textures: a functional magnetic resonance imaging study, J. Neurosci., 16, 5205, 10.1523/JNEUROSCI.16-16-05205.1996

Rorden, 2007, Improving lesion-symptom mapping, J. Cogn. Neurosci., 19, 1081, 10.1162/jocn.2007.19.7.1081

Samson, 2004, Left temporoparietal junction is necessary for representing someone else's belief, Nat. Neurosci., 7, 499, 10.1038/nn1223

Satterthwaite, 2013, An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data, Neuroimage, 64, 240, 10.1016/j.neuroimage.2012.08.052

Schultz, 2005, Developmental deficits in social perception in autism: the role of the amygdala and fusiform face area, Int. J. Dev. Neurosci., 23, 125, 10.1016/j.ijdevneu.2004.12.012

Spielberger, 1983

Tager-Flusberg

Wang, 2012, Extracting multiscale pattern information of fMRI based functional brain connectivity with application on classification of autism spectrum disorders, PLoS One, 7, e45502, 10.1371/journal.pone.0045502

World Health Organization, 1992, The ICD-10 classification of mental and behavioural disorders, Int. Classif., 10, 1

Zhang, 2011, Distinct resting-state brain activities in heroin-dependent individuals, Brain Res., 1402, 46, 10.1016/j.brainres.2011.05.054

Zhou, 2014, Multiparametric MRI characterization and prediction in autism spectrum disorder using graph theory and machine learning, PLoS One, 9, e90405, 10.1371/journal.pone.0090405

Zilbovicius, 2006, Autism, the superior temporal sulcus and social perception, Trends Neurosci., 29, 359, 10.1016/j.tins.2006.06.004