Publications


2022

  • Nicolaisen-Sobesky E, Mihalik A, Kharabian-Masouleh S, Ferreira FS, Hoffstaedter F, Schwender H, Maleki Balajoo S, Valk SL, Eickhoff SB, Yeo BTT, Mourao-Miranda J & Genon S. A cross-cohort replicable and heritable latent dimension linking behaviour to multi-featured brain structure.. Nature Communications Biology, 2022. Available here.

  • Mihalik A, Chapman J, Adams RA, Winter N, Ferreira FS, Shawe-Taylor J, Mourao-Miranda J. Canonical Correlation Analysis and Partial Least Squares for identifying brain-behaviour associations: a tutorial and a comparative study. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2022. Available here.

  • Ferreira FS, Mihalik A, Adams RA, Ashburner J, Mourao-Miranda J. A hierarchical Bayesian model to find brain-behaviour associations in incomplete data sets. NeuroImage, 2022. Available here.

  • Toron N, Mourao-Miranda J, Shawe-Taylor J. TransductGAN: a Transductive Adversarial Model for Novelty Detection. arXiv, 2022. Available here.

2021

  • Brown C,William Story G, Mourao-Miranda J and Taylor Baker J. Will artificial intelligence eventually replace psychiatrists? . Br J Psychiatry, March 2021. Available here.

  • Ferreira FS, Mihalik A, Adams RA, Ashburner J, Mourao-Miranda J. A hierarchical Bayesian model to find brain-behaviour associations in incomplete data sets. arXiv, 2021. Available here.

2020

  • Schulz MA, Yeo BTT, Vogelstein JT, Mourao-Miranda J, Kather JN, Kording K, Richards B and Bzdok D. Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets. Nature Communications, August 2020. Available here.

  • Fernandes O, Lima Portugal LC, de Cássia SAR, Arruda-Sanchez T, Volchan E, Garcia Pereira M, Mourao-Miranda J, Oliveira L. How do you perceive threat? It is all in your pattern of brain activity. Brain Imaging and Behavior, 2020. Available here.

  • Wang HT, Smallwood J, Mourao-Miranda J , Xia CD, Satterthwaite TD, Bassett DS, Bzdok D. Finding the needle in a high-dimensional haystack: Canonical correlation analysis for neuroscientists. NeuroImage, 2020. Available here.

  • Browning M, Carter CS, Chatham C, Den Ouden H, Gillan CM, Baker JT, Chekroud AM, Cools R, Dayan P, Gold J, Goldstein RZ, Hartley CA, Kepecs A, Lawson RP, Mourao-Miranda J, Phillips ML, Pizzagalli DA, Albert Powers, Rindskopf D, Roiser JP, Schmack, K Schiller D, Sebold M, Stephan KE, Frank MJ, Huys Q, Paulus M. Realizing the clinical potential of computational psychiatry: report from the Banbury Center Meeting, February 2019. Biological Psychiatry, 2020. Available here.

  • Mihalik A, Adams RA, Huys Q. Canonical correlation analysis for identifying biotypes of depression. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2020. Available here.

  • Mihalik A, Ferreira FS, Moutoussis M, Ziegler G, Adams RA, Rosa MJ, Prabhu G, Oliveira L, Pereira M, Bullmore E, Fonagy P, Goodyer IM, Jones PB, Shawe-Taylor J, Dolan RJ, Mourao-Miranda J. Multiple Holdouts With Stability: Improving the Generalizability of Machine Learning Analyses of Brain-Behavior Relationships. Biological Psychiatry, 2020. Available here.
  • Schrouff J, Raccah O, Baek s, Rangarajan V, Salehi S, Mourao-Miranda J, Zeinab Helili, Daitch AL, Parvizi J. Fast temporal dynamics and causal relevance of face processing in the human temporal cortex. Nature Communications, 2020. Available here.

2019

  • Brown C, Story GW, Mourao-Miranda J, Baker JT. Will artificial intelligence eventually replace psychiatrists?. The British Journal of Psychiatry, 2019. Available here.

  • Schulz M, Yeo BTT, Vogelstein JT, Mourao-Miranda J, Kather JN, Kording K, Richards B, Bzdok D. Deep learning for brains?: Different linear and nonlinear scaling in UK Biobank brain images vs. machine-learning datasets. Preprint in bioRxiv, 2019. Available here.

  • Fernandes O, Portugal LCL, Alves RCS, Arruda-Sanchez T,Volchan E, Pereira MG, Mourao-Miranda J, Oliveira L. How do you perceive threat? It’s all in your pattern of brain activity. Brain Imaging and Behavior, 2019. Available here.

  • Browning M, Carter C, Chatham C, Ouden H, Gillan C, Baker J, Chekroud A, Cools R, Dayan P, Gold J, Goldstein R, Hartley C, Kepecs A, Lawson R, Mourao-Miranda J, Phillips M, Pizzagalli D, Powers A, Rindskopf D, Roiser J, Schmack K, Schiller D, Sebold M, Stephan KE, Frank MJ, Huys Q, Paulus M. Realizing the Clinical Potential of Computational Psychiatry: Report from the Banbury Center Meeting, February 2019. Preprint in PsyArXiv, 2019. Available here.

  • Mihalik A*, Ferreira FS*, Rosa MJ, Moutoussis M, Ziegler G, Monteiro JM, Portugal L, Adams RA, Romero-Garcia R, Vertes P, Kitzbichler MG, Vasa F, Vaghi MM, Bullmore E, Fonagy P, Goodyer IM, Jones PB, Dolan RJ, Mourao-Miranda J. Brain-behaviour modes of covariation in healthy and clinically depressed young people. Scientific Reports, 2019. Available here. *these authors contributed equally to this work.

  • Mihalik A*, Brudfors M*, Robu M, Ferreira FS, Lin H, Rau A, Wu T, Blumberg SB, Kanber B, Tariq M, Garcia MDME, Zor C, Nikitichev DI, Mourao-Miranda J#, Oxtoby NP#. ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression. Preprint in arXiv, 2019. Available here. #*these authors contributed equally to this work.

  • Oxtoby NP*, Ferreira FS*, Mihalik A, Wu T, Brudfors M, Lin H, Rau A, Blumberg SB, Robu M, Zor C, Tariq M, Garcia MDME, Kanber B, Nikitichev DI, Mourao-Miranda J. ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology. Preprint in arXiv, 2019. Available here. *these authors contributed equally to this work.

  • Oliveira L, Portugal LCL, Pereira M, Chase HW, Bertocci M, Stiffler R, Greenberg T, Bebko G, Lockovich J, Aslam H, Mourao-Miranda J*, Phillips ML*. Predicting Bipolar Disorder risk factors in distressed young adults from patterns of brain activation to reward: a machine learning approach. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2019. Available here. *these authors contributed equally to this work.

  • Donini M, Monteiro JM, Pontil M, Hahn T, Fallgatter AJ, Shawe-Taylor J, Mourao-Miranda J. Combining heterogeneous data sources for neuroimaging based diagnosis: re-weighting and selecting what is important. Neuroimage, 2019. Available here

  • Portugal LCL, Schrouff J, Stiffler R, Bertocci M, Bebko G, Chase H, Lockovitch J, Aslam H, Graur S, Greenberg T, Pereira M, Oliveira L, Phillips M, Mourao-Miranda J. Predicting anxiety from wholebrain activity patterns to emotional faces in young adults: A machine learning approach. Neuroimage: Clinical, 2019. Available here

2018

  • Wang H, Smallwood J, Mourao-Miranda J, Xia CH, Satterthwaite TD, Bassett DS, Bzdok D. Finding the needle in high-dimensional haystack: A tutorial on canonical correlation analysis. Preprint in arXiv, 2018. Available here

  • Altmann A, Mourao-Miranda J. Evidence for bias of genetic ancestry in resting state functional MRI. Preprint in bioRxiv, 2018. Available here

  • Schrouff J, Mourao-Miranda J. Interpreting weight maps in terms of cognitive or clinical neuroscience: nonsense?. International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2018. Available here

  • Ferreira FS, Rosa MJ, Moutoussis M, Dolan R, Shawe-Taylor J, Ashburner J, Mourao-Miranda J. Sparse PLS hyper-parameters optimisation for investigating brain-behaviour relationships. International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2018. Available here

  • Janssen RJ, Mourao-Miranda J, Schnack, HG. Making individual prognoses in psychiatry using neuroimaging and machine learning. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2018. Available here

  • Schrouff J, Monteiro JM, Portugal L, Rosa MJ, Phillips C, Mourao-Miranda J. Embedding anatomical or functional knowledge in whole-brain multiple kernel learning models. Neuroinformatics, 2018. Available here

2017

  • Monteiro JM. Exploring the latent space between brain and behaviour using eigen-decomposition methods. PhD dissertation. Available here

  • Rao A, Mourao-Miranda J. Feature Adjustment in Kernel Space when using Cross-Validation. Research Note - UCL Department of Computer Science, 2017. Available here

  • Baldassarre L, Pontil, M, Mourao-Miranda J. Sparsity is better with stability: combining accuracy and stability for model selection in brain decoding. Frontiers in Neuroscience: Brain Imaging Methods, 2017. Available here

  • Rao A, Monteiro J, Mourao-Miranda J. Predictive Modelling using Neuroimaging Data in the Presence of Confounds. Neuroimage, 2017. Available here

  • Nieuwenhuis M, Schnack HG, van Haren NE, Lappin J, Morgan C, Reinders AA, Gutierrez-Tordesillas D, Roiz-Santianez R, Schaufelberger MS, Rosa PG, Zanetti MV, Busatto GF, Crespo-Facorro B, McGorry PD, Velakoulis D, Pantelis C, Wood SJ, Kahn RS, Mourao-Miranda J*, Dazzan P*. Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients. Neuroimage, 2017, S1053-8119(16)30334-2 *these authors contributed equally to this work.

  • Fernandes OF, Portugal L, Alves C, Arruda-Sanchez T, Rao A, Volchan E, Pereira M, Oliveira L, Mourao-Miranda J. Decoding negative affect personality trait from patterns of brain activation to threat stimuli. Neuroimage, 2017, S1053-8119(15)01163-5

  • Calhoun VD, Lawrie SM, Mourao-Miranda J, Stephan KE. Prediction of Individual Differences from Neuroimaging Data. Neuroimage, 2017. Available here

2016

  • Donini M, Monteiro, J, Pontil, M, Shawe-Taylor, J, Mourao-Miranda J. A multimodal multiple kernel learning approach to Alzheimer's disease detection. IEEE Int. Workshop on Machine Learning for Signal Processsing, 2016. Available here

  • Schrouff J, Mourao-Miranda J. , Phillips C, Parvizi J. Decoding intracranial EEG data with multiple kernel learning method. J. Neurosci. Methods., 2016, 261:19-28

  • Rao A, Monteiro JM, Mourao-Miranda J. Prediction of clinical scores from neuroimaging data with censored likelihood gaussian processes. International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2016. Available here

  • Monteiro JM, Rao A, Shawe-Taylor J, Mourao-Miranda J; Alzheimer's Disease Initiative. A multiple hold-out framework for Sparse Partial Least Squares. J Neurosci Methods., 2016, S0165-0270(16)30132-7

  • Portugal L, Rosa MJ, Rao A, Bebko G, ..., Pereira M, Oliveira L, Phillips ML*, Mourao-Miranda J*.Can emotional and behavioral dysregulation in youth be decoded from functional neuroimaging? PLoS one, 2016 *these authors contributed equally to this work.

2015

  • Monteiro JM, Rao A, Ashburner J, Shawe-Taylor J, Mourao-Miranda J. Multivariate effect ranking via adaptive sparse PLS.International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2015. Available here

  • Schrouff J, Phillips C, Parvizi P, Mourao-Miranda J. Predicting numerical processing in naturalistic settings from controlled experimental conditions.International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2015. Available here

  • Rao A, Monteiro JM, Ashburner J, Portugal L, Fernandes O, Oliveira L, Pereira M, Mourao-Miranda J. A Comparison of Strategies for Incorporating Nuisance Variables into Predictive Neuroimaging Models.International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2015.Available here

  • Rosa MJ, Portugal L, Hahn T, Fallgatter AJ, Garrido M, Shawe-Taylor J, Mourao-Miranda J. Sparse network-based models for patient classification using fMRI. Neuroimage, 2015, 105:493-506

2014

  • Monteiro JM, Rao A, Ashburner J, Shawe-Taylor J, Mourao-Miranda J. Leveraging Clinical Data to Enhance Localisation of Brain Atrophy. Machine Learning and Interpretation in Neuroimaging (MLINI), 2014

  • Rocha-Rego V, Jogia J, Marquand AF, Mourao-Miranda J, Simmons A, Frangou S. Examination of the predictive value of structural magnetic resonance scans in bipolar disorder: a pattern classification approach. Psychol Med. 2013 Jun 5:1-14.

  • Evans S, Kyong JS, Rosen S, Golestani N, Warren JE, McGettigan C, Mourao-Miranda J, Wise, RJ, Scott SK. The Pathways for Intelligible Speech: Multivariate and Univariate Perspectives. Cereb Cortex. 2013 Apr 12.

2013

  • Rondina J, Hahn T, de Oliveira L, Marquand A, Dresler T, Leitner T, Fallgatter A, Shawe-Taylor J, Mourao-Miranda J. SCoRS - a method based on stability for feature selection and mapping in neuroimaging. IEEE Trans Med Imaging. 2013 Sep 11. Available

  • Almeida JR, Mourao-Miranda J, Aizenstein HJ, Versace A, Kozel FA, Lu H, Marquand A, Labarbara EJ, Brammer M, Trivedi M, Kupfer DJ, Phillips ML. Pattern recognition analysis of anterior cingulate cortex blood flow to classify depression polarity. Br J Psychiatry. 2013 Oct;203:310-1.

  • Schrouff J, Cremers J, Garraux G, Baldassarre L, Mourao-Miranda J, Phillips C. Localizing and Comparing Weight Maps Generated from Linear Kernel Machine Learning Models. International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2013. Available here

  • Rosa MJ, Portugal L, Shawe-Taylor J, Mourao-Miranda J. Sparse Network-Based Models for Patient Classification Using fMRI. International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2013. Available here

  • Rondina JM, Shawe-Taylor J, Mourao-Miranda J. Stability-Based Multivariate Mapping Using SCoRS. International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2013. Available here

  • Marquand AF, Filippone M, Ashburner J, Girolami M, Mourao-Miranda J, Barker GJ, Williams SC, Leigh PN, Blain CR. Automated, high accuracy classification of parkinsonian disorders: a pattern recognition approach. PLoS One, 2013 Jul 15;8(7):e69237.

  • Oliveira L, Ladouceur CD, Phillips ML, Brammer M, Mourao-Miranda J. What does brain response to neutral faces tell us about major depression? Evidence from machine learning and fMRI. PLoS ONE, 2013;8(4):e60121.

  • Schrouff J*, Rosa MJ*, Rondina J, Marquand A, Chu C, Ashburner J, Phillips C, Richiardi J, Mourao-Miranda J. PRoNTo: Pattern Recognition for Neuroimaging Toolbox, Neuroinformatics, February 2013. *these authors contributed equally to this work.

2012

  • Mourao-Miranda J, Rondina JM, Portugal L, Shawe-Taylor J. Elastic-net Multiple Kernel Learning for multi-region neuroimaging based diagnosis. Proceedings of the 2nd NIPS Workshop on Machine Learning and Interpretation in Neuroimaging 2012. Available here

  • Sato JR, Rondina JM, Mourao-Miranda J. Measuring abnormal brains: building normative rules in neuroimaging using one-class support vector machines. Front Neurosci. 2012, 6:178.

  • Mourao-Miranda J, Almeida J, Hassel S, de Oliveira L, Versace A, Marquand A, Sato J, Brammer M, Phillips M. Pattern recognition analyses of brain activation elicited by happy and neutral faces in unipolar and bipolar depression. Bipolar Disorders 2012, 14(4):451-60.

  • Filippone M, Marquand A, Blain C, Williams C, Mourao-Miranda J, Girolami M. Probabilistic prediction of neurological disorders with a statistical assessement of neuroimaging data modalities. Annals of Applied Statistics.

  • Baldassarre L, Mourao-Miranda J, Pontil M. Structured Sparsity Models for Brain Decoding from fMRI data, International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2012

  • Hahn T*, Marquand AF*, Plichta MM, Ehlis A, Schecklmann MW, Dresler T, Jarczok TA, Eirich E, Leonhard C, Reif A, Lesch K, Brammer MJ, Mourao-Miranda J, Fallgatter AF. A novel approach to probabilistic biomarker-based classification using functional near-infrared spectroscopy. Human Brain Mapping, 2012. *these authors contributed equally to this work.

  • Mourao-Miranda J*, de Oliveira L*, Ladouceur CD, Marchand A, Birmaher B, Axelson D, Phillips ML. Pattern recognition and functional neuroimaging help to discriminate healthy adolescents at risk for mood disorders from low risk adolescents. PLoS ONE, 2012 7(2):e29482. *these authors contributed equally to this work.

  • Kloppel S, Abdulkadir A, Jack CR Jr, Koutsouleris N, Mourao-Miranda J, Vemuri P. Diagnostic neuroimaging across diseases. Neuroimage. 2011 Nov 7.

  • Mourao-Miranda J, Reinders AA, Rocha-Rego V, Lappin J, Rondina J, Morgan C, Morgan KD, Fearon P, Jones PB, Doody GA, Murray RM, Kapur S, Dazzan P. Individualised Prediction of Illness Course at the First Psychotic Episode: a Support Vector Machine MRI Study. Psychological Medicine, Nov 7:1-11, 2011

2011

  • Rondina JM, Shawe-Taylor J, Mourao-Miranda J. A new feature selection method - evaluating stability and classification accuracy in neuroimaging data. NIPS 2011 Workshop: Machine Learning and Interpretation in Neuroimaging. Sierra Nevada, Spain, 2011.

  • Mourao-Miranda J, Hardoon DR, Hahn T, Marquand AF, Williams SC, Shawe-Taylor J, Brammer M. Patient Classification as an Outlier Detection Problem: an Application of the One-Class Support Vector Machine. Neuroimage. 2011 Oct 1;58(3):793-804.

  • Chu C, Mourao-Miranda J, Chiu YC, Kriegeskorte N, Tan G, Ashburner J. Utilizing temporal information in fMRI decoding: Classifier using kernel regression methods. Neuroimage. 2011 Sep 15;58(2):560-71.

  • Marquand AF, De Simoni S, O'Daly OG, Williams SC, Mourao-Miranda J, Mehta MA. Pattern classification of working memory networks reveals differential effects of methylphenidate, atomoxetine, and placebo in healthy volunteers. Neuropsychopharmacology. 2011.

  • Hahn T, Marquand AF, Ehlis AC, Dresler T, Kittel-Schneider S, Jarczok TA, Lesch KP, Jakob PM, Mourao-Miranda J, Brammer MJ, Fallgatter AJ. Integrating Neurobiological Markers of Depression. Arch Gen Psychiatry. 2011.

2010

  • Ecker C, Marquand A, Mourao-Miranda J, Johnston P, Daly EM, Brammer MJ, Maltezos S, Murphy CM, Robertson D, Williams SC, Murphy DG. Describing the brain in autism in five dimensions--magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach. J Neurosci. 2010.

  • Marquand A, De Simoni S, O'Daly O G, Mehta M A, Mourao-Miranda J. Quantifying the Information Content of Brain Voxels using Target Information, Gaussian Processes and Recursive Feature Elimination. First Workshop on Brain Decoding: Pattern Recognition Challenges in Neuroimaging at the International Conference on Pattern Recognition (ICPR). IEEE CONFERENCES. 2010.

  • Marquand A, Howard M, Brammer M, Chu C, Coen S, Mourao-Miranda J. Quantitative prediction of subjective pain intensity from whole-brain fMRI data using Gaussian processes. NeuroImage 2010.

  • Szameitat AJ, Raabe M, Muller HJ, Greenlee MW, Mourao-Miranda J, NCP Students. Motor imagery of voluntary coughing: a functional MRI study using a support vector machine. Neuroreport 2010.

  • Plant C, Teipel SJ, Oswald A, Bohm C, Meindl T, Mourao-Miranda J, Bokde AW, Hampel H, Ewers M. Automated detection of brain atrophy patterns based on MRI for the prediction of Alzheimer's disease. Neuroimage 2010.

  • Ecker C, Rocha-Rego V, Johnston P, Mourao-Miranda J, Marquand A, Daly EM, Brammer MJ, Murphy C, Murphy DG; MRC AIMS Consortium. Investigating the predictive value of whole-brain structural MR scans in Autism: a pattern classification approach. NeuroImage 2010.

2009

  • Sato JR, Fujita A, Thomaz CE, Martin Mda G, Mourao-Miranda J, Brammer MJ, Amaro Junior E. Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction. NeuroImage 2009.

  • Costafreda SG, Khanna A, Mourao-Miranda J, Fu CH. Neural correlates of sad faces predict clinical remission to cognitive behavioural therapy in depression. Neuroreport. 2009.

  • Hardoon DR, Ettinger U, Mourao-Miranda J, Antonova E, Collier D, Kumari V, Williams SC, Brammer M. Correlation-based multivariate analysis of genetic influence on brain volume. Neurosci Lett. 2009.

  • Mourao-Miranda J, Ecker C, Sato JR, Brammer M. Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data. J Cogn Neurosci. 2008.

  • Sato JR, da Graca Morais Martin M, Fujita A, Mourao-Miranda J, Brammer MJ, Amaro E Jr. An fMRI normative database for connectivity networks using one-class support vector machines. Human Brain Mapping, 2008.

2008

  • Marquand AF, Mourao-Miranda J, Brammer MJ, Cleare AJ, Fu CH. Neuroanatomy of verbal working memory as a diagnostic biomarker for depression. Neuroreport. 2008.

  • Sato JR, Mourao-Miranda J, Morais Martin Mda G, Amaro E Jr, Morettin PA, Brammer MJ. The impact of functional connectivity changes on support vector machines mapping of fMRI data. J. Neurosci Methods. 2008.

  • Friston K, Chu C, Mourao-Miranda J, Hulme O, Rees G, Penny W, Ashburner J. Bayesian decoding of brain images. NeuroImage, 2008.

  • Fu CH, Mourao-Miranda J, Costafreda SG, Khanna A, Marquand AF, Williams SC, Brammer MJ. Pattern classification of the neural correlates of sad facial processing: towards diagnostic toll for depression. Biological Psychiatry, 2008.

2007

  • Mourao-Miranda J, Friston KJ, Brammer M. Dynamic discrimination analysis: A spatial-temporal SVM. NeuroImage, 2007.

  • Hardoon DR, Mourao-Miranda J, Brammer M, Shawe-Taylor J. Unsupervised analysis of fMRI data using Kernel Canonical Correlation. NeuroImage, 2007.

  • Sato JR, Fujita A, Amaro E Jr, Mourao-Miranda J, Morettin PA, Brammer MJ. DWT-CEM: An Algorithm for Scale-Temporal Clustering in fMRI. Biological Cybernetics, 2007.

2006

  • Mourao-Miranda J, Reynaud E, McGlone F, Calvert G, Brammer M. The impact of temporal compression and space selection on SVM analysis of single-subject and multi-subject fMRI data. NeuroImage, 2006.

2005

  • Mourao-Miranda J, Bokde AL, Born C, Hampel H, Stetter M. Classifying brain states and determining the discriminating activation patterns: support vector machine on functional MRI data. NeuroImage, 2005.