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Dr Andre Marquand

PhD

Lecturer

 

Contact Details

Email: Andre.Marquand@kcl.ac.uk

Telephone / Fax: 020 3228 3066 / 2116

Location: Room 3.08 , Centre for Neuroimaging Sciences

Address: Institute of Psychiatry, PO89, De Crespigny Park, London SE5 8AF, U.K.

 

Biography

I am interested in the application of machine learning and pattern recognition methods to neuroimaging and other neuroscientific data to further the understanding of human brain function. Such methods aim to learn to detect patterns of statistical regularity in empirical data and hold significant promise for decoding cognitive states and predicting clinically relevant variables in health and disease.

 


Publications

Publications (Five year Impact factor (IF) and journal rank within ISI subject category given in brackets)

*: joint first authorship

  1. Schmaal, L.*, Marquand A.*, et al. (in press) Predicting the naturalistic course of major depressive disorder using clinical and multimodal neuroimaging information: a multivariate pattern recognition study. Biological Psychiatry [IF = 10.3, rank = 4/136]

  2. O'Muircheartaigh, J., Marquand A. et al. (in press) Multivariate decoding of cerebral blood flow measures in a clinical model of on-going postsurgical pain. Hum Brain Mapp. [IF = 6.9, rank = 1/14]

  3. Rondina, J., Hahn, T., Marquand A., et al (in press) SCoRS - a method based on stability for feature selection and mapping in neuroimaging. IEEE Transactions on Medical Imaging [IF = 4.6, rank 6/102]

  4. Hart, H., Chantiluke, K., Cubillo, A., Smith, A., Simmonds, A., Brammer, M., Marquand A., Rubia K. (2014) Pattern classification of response inhibition in ADHD: toward the development of neurobiological markers for ADHD. Hum Brain Mapp, 35, 3083-94 [IF = 6.9, rank 1/14]

  5. Marquand A., Brammer, M., Williams, S., Doyle O (2014) Bayesian multi-task learning for decoding multi-subject neuroimaging data Neuroimage, 92, 298-311 [IF = 6.9, rank = 1/14]

  6. Hart H., Marquand, A., et al (2014). Predictive neurofunctional markers of ADHD based on pattern classification of temporal processing J Child and Adol Psych 53, 569-78 [IF = 7.4, rank = 9/136]

  7. Rocha-Rego V., Jogia, J., Marquand A. et al (2014) Examination of the predictive value of structural magnetic resonance scans in bipolar disorder: a pattern classification approach. Psych Medicine 44, 519-32  [IF = 6.5, rank = 12/136]

  8. Gong, Q., Tognin, S., Pettersson-Yeo, W., Marquand, A. et al (2014) Multivariate analysis of structural MRI identifies trauma survivors with and without Post-Traumatic Stress Disorder with high accuracy Psychological Medicine 44, 195-203 [IF = 6.5, rank = 12/136]

  9. Doyle O., Westman E, Marquand A., et al. (2014) Predicting progression of Alzheimer's disease using ordinal regression. PLOS ONE. 9 e105542 [IF = 4.0, rank = 7/55]

  10. Frick A., Gingnell, M. Marquand A. et al (2014) Classifying social anxiety disorder using multivoxel pattern analysis of brain function and structure. Behav Brain Res 259, 330-35 [IF = 3.6, rank = 105/252]

  11. Pettersson-Yeo, W., Benetti, S., Marquand, A. et al (2014) An empirical comparison of different approaches for combining multimodal neuroimaging data with support vector machine. Front Neurosci  8, 189 [no IF]

  12. Marquand A. et al (2014) Full Bayesian multi-task learning for multi-output brain decoding and accommodating missing data,  International Workshop in Pattern Recognition in Neuroimaging, Tuebingen, Germany

  13. O’Harney, A., Marquand A., et al (2014) Pseudo-Marginal Bayesian Multiple-Class Multiple-Kernel Learning for Neuroimaging Data. 22nd International Conference on Pattern Recognition (ICPR), 2014

  14. Almeida, J., Mourao-Miranda, J., Aizenstein, H., Versace, A., Kozel, F., Lu, H., Marquand, A. et al (2013) Pattern recognition analysis of anterior cingulate cortex blood flow to classify depression polarity. Br J Psych 203, 310-1.

  15. Marquand, A., Filippone, M. et al (2013) Automated, high accuracy classification of Parkinsonian disorders: a pattern recognition approach. PLOS ONE 8, e69237 [IF = 4.0, rank = 7/55]

  16. Doyle O., Ashburner, J., Zelaya, F, Williams, S., Mehta, M, Marquand, A. (2013) Multivariate decoding of brain images using ordinal regression. Neuroimage 81, 347-57 [IF = 6.9, rank = 1/14]

  17. Hahn, T.*, Marquand, A.*, Plichta, M. et al. (2013) A novel approach to probabilistic biomarker-based classification using functional Near-Infrared Spectroscopy, Human Brain Mapping 34, 1102-14 [IF = 6.9, rank = 1/14]

  18. Lim, L., Marquand A. et al (2013) Disorder-specific predictive classification of adolescents with attention-deficit hyperactivity disorder relative to autism using structural magnetic resonance imaging PLOS ONE 8, e63660 [IF = 4.0, rank = 7/55]

  19. Schrouff, J., Rosa, M., Rondina, J., Marquand A. et al (2013). Pronto: Pattern Recognition for Neuroimaging Toolbox. Neuroinformatics 11, 319-37 [IF = 2.9, rank = 134/252]

  20. Deeley, Q., Oakley, D., Toone, B., Bell V., Walsh, E., Marquand, A. et al (2013). The functional anatomy of suggested limb paralysis. Cortex 49, 411-22 [IF = 8.4, rank = 19/252]

  21. De Simoni, S., Schwarz, A., O'Daly, O., Marquand, A. et al (2013) Test-retest reliability of the BOLD pharmacological MRI response to ketamine in healthy volunteers. Neuroimage 64, 75-90 [IF = 6.9, rank = 1/14]

  22. Marquand, A., Rosa, M. J., Doyle, O. (2013) Conditional Gaussian graphical models for multi-output regression of neuroimaging data. International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines, Leuven Belgium

  23. Schrouff, J., Rosa, M., Rondina, J., Marquand, A., Chu C., Ashburner, J., Richiardi, J., Phillips C., Mourão-Miranda, J. (2013) Pattern recognition for neuroimaging toolbox. International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines, Leuven Belgium

  24. Schrouff, J., Rosa, M., Rondina, J., Marquand, A., Chu C., Ashburner, J., Phillips C., Richiardi, J., Mourão-Miranda, J. (2013) Multivariate pattern interpretation using PRoNTo Pattern Recognition in Neuroimaging, Pittsburg, U.S.A.
  1. Pettersson-Yeo, W., Benetti, S., Marquand A. (2013) et al Using genetic, cognitive and multi-modal neuroimaging data to identify ultra-high-risk and first-episode psychosis at the individual level Psychological  Medicine 14, 1-16 [IF = 6.5, rank = 12/136]

  2. Marquand A., O’Daly, O., De Simoni S., Allsop, D., Maguire, R. P., Williams, S., Zelaya, F., Mehta, M. (2012). Dissociable effects of methylphenidate, atomoxetine and placebo on regional cerebral blood flow in healthy volunteers at rest: a multi-class pattern recognition approach. NeuroImage 36, 1237-47 [IF = 6.9, rank = 1/14]

  3. Filippone, M., Marquand A., et al (2012). Probabilistic prediction of neurological disorders with a statistical assessment of neuroimaging data modalities. Annals of Applied Statistics 6, 1883-1905 [IF = 2.4, rank = 12/119]

  4. Mourao-Miranda J., Almeida, J. Hassel, S., De Oliveira L., Versace, A., Marquand A. et al. (2012). Pattern recognition analyses of brain activation elicited by happy and neutral faces in unipolar and bipolar depression. Bipolar Disorders 14, 451-60 [IF = 5.5, rank = 17/136]

  5. Mourao-Miranda, J., Olivera, L., Ladoucer, C., Marquand, A., et al (2012). Machine learning and neuroimaging predict future mental illness in at-risk adolescents, PLOS ONE 7, e29482 [IF = 4.0, rank = 7/55]

  6. Orrù, G., Pettersson-Yeo W., Marquand A., Sartori G., Mechelli. A. (2012) Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: A critical review. Neuroscience and Biobehavioural Reviews 36, 1140-52 [IF = 11.1, rank = 10/252]

  7. Marquand A., De Simoni S., O’Daly, O., Williams, S., Mourao-Miranda, J., Mehta, M. (2011) Pattern classification of working memory networks reveals differential effects of methylphenidate, atomoxetine and placebo in healthy volunteers. Neuropsychopharmacology 36, 1237-47 [IF = 8.5, rank = 6/136]

  8. Hahn, T., Marquand, A., Ehlis, A., Dresler, T., Kittel-Schneider, S., Jarczok, T., et al. (2011) Integrating neurobiological markers of depression. Archives of General Psychiatry 68, 361-8 [IF = 14.4, rank = 2/136]

  9. Mourao-Miranda, J., Hardoon, D., Hahn, T., Marquand A., et al (2011). Patient classification as an outlier detection problem: an application of the one-class support vector machine. NeuroImage 58,793-804 [IF = 6.9, rank = 1/14]

  10. Gong, Q., Lui, S., Jiaa, Z., Marquand, A., Scarpazza C., McGuire, P. Mechelli, A. (2011). Predicting therapeutic response in depression with MRI: a support vector machine study. Neuroimage 55, 1497-503 [IF = 6.9, rank = 1/14]

  11. Doyle, O., Mehta, M., Brammer, M., Schwarz, A., Marquand, A. (2011) Data-driven modeling of BOLD drug response curves using Gaussian process learning. Workshop on Machine Learning and Interpretability in Neuroimaging, Neural Information Processing Systems, Granada, Spain

  12. Marquand, A., Howard M., Brammer, M., Chu, C., et al. (2010). Quantitative prediction of subjective pain intensity from whole-brain fMRI data using Gaussian processes. NeuroImage 126, 272-7. [IF = 6.9, rank = 1/14]

  13. Ecker, C., Marquand, A., Mourão-Miranda, J., Johnston, P., Daly E. et al. (2010). Describing the brain in autism in five dimensions – magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach. Journal of Neuroscience 30, 10612-23 [IF 7.6, rank = 21/252]

  14. Ecker, C., Rocha-Rego, V., Mourão-Miranda, J., Marquand, A., et al. (2010) Investigating the predictive value of whole-brain structural MR scans in autism: a pattern classification approach. NeuroImage 49, 44-56 [IF = 6.9, rank = 1/14]
  1. Cole, J., Toga A., Hojatkashani C., Thompson P., Costafreda S., Cleare A., Williams S., Bullmore E., Scott J., Mitterschiffthaler M., Walsh N., Donaldson C., Mirza M., Marquand A.  et al (2010) Subregional hippocampal deformations in major depressive disorder J Affect Disord 126, 272. [IF = 4.2, rank = 30/136]

  2. Marquand, A., De Simoni, S, O’Daly, O., Mourao-Miranda, J., et al. (2010). Quantifying the information content of brain voxels using target information, Gaussian processes and recursive feature elimination. Workshop on Brain Decoding, International Conference on Pattern Recognition, Istanbul, Turkey

  3. Chu, C., Bandettini, P., Ashburner, J., Marquand, A., Kloeppel, S. (2010). Classification of neurodegenerative diseases using Gaussian process classification with automatic feature determination., International Conference on Pattern Recognition, Istanbul, Turkey

  4. Marquand, A., Mourão-Miranda, J., Brammer, M., Cleare, A., Fu, C. (2008). Neuroanatomy of verbal working memory as a diagnostic biomarker for depression. Neuroreport 19, 1507-11. [IF = 1.8, rank = 196/252]

  5. Fu, C., Mourão-Miranda, J., Costafreda, S., Khanna, A., Marquand, A. et al., (2008). Pattern classification of sad facial processing: towards the development of neurobiological markers in depression. Biol Psych 63, 656-62 [IF = 10.3, rank = 4/136] 
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