M. J. Rosa

发表

Classification and characterisation of brain network changes in chronic back pain: A multicenter study.

B. Seymour, M. Kawato, W. Yoshida, 2018, Wellcome open research.

Time Scales of Representation in the Human Brain: Weighing Past Information to Predict Future Events

W. Penny, L. Harrison, G. Green, 2011, Front. Hum. Neurosci..

EEG-fMRI integration: a critical review of biophysical modeling and data analysis approaches.

Karl J. Friston, J. Daunizeau, M. J. Rosa, 2010, Journal of integrative neuroscience.

Associations between polygenic risk scores for four psychiatric illnesses and brain structure using multivariate pattern recognition

M. Mehta, D. Dima, M. J. Rosa, 2018, NeuroImage: Clinical.

Connectivity Changes Underlying Neurofeedback Training of Visual Cortex Activity

Geraint Rees, Nikolaus Weiskopf, Chloe Hutton, 2014, PloS one.

The role of the subgenual anterior cingulate cortex in dorsomedial prefrontal–amygdala neural circuitry during positive‐social emotion regulation

F. Scharnowski, P. Vuilleumier, S. Eickhoff, 2020, Human brain mapping.

Classification and characterisation of brain network changes in chronic back pain: A multicenter study

Kenji Leibnitz, Mitsuo Kawato, Nicholas Shenker, 2017, bioRxiv.

Auditory prediction errors as individual biomarkers of schizophrenia

Jeremy A. Taylor, M. Garrido, P. Michie, 2017, NeuroImage: Clinical.

Auditory prediction errors as individual biomarkers of schizophrenia

M. Garrido, P. Michie, M. J. Rosa, 2017, bioRxiv.

Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

S. Holland, M. Phillips, E. Forbes, 2016, PloS one.

Posterior Probability Maps

M. J. Rosa, 2015 .

Brain-behaviour modes of covariation in healthy and clinically depressed young people

Peter B. Jones, Fabio S. Ferreira, R. Dolan, 2018, Scientific Reports.

Brain-behaviour modes of covariation in healthy and clinically depressed young people

Michael Moutoussis, Peter Fonagy, Edward T. Bullmore, 2018, bioRxiv.

Bayesian model selection maps for group studies

William D. Penny, Lee M. Harrison, Sven Bestmann, 2009, NeuroImage.

PRoNTo: Pattern Recognition for Neuroimaging Toolbox

Janaina Mourão Miranda, Christophe Phillips, Jonas Richiardi, 2013, Neuroinformatics.

Development and application of model selection methods for investigating brain function

Maria João Duarte Rosa, M. J. Rosa, 2012 .

Bayesian Comparison of Neurovascular Coupling Models Using EEG-fMRI

William D. Penny, James Kilner, Maria J. Rosa, 2011, PLoS Comput. Biol..

Connectivity-based neurofeedback: Dynamic causal modeling for real-time fMRI☆

Dimitri Van De Ville, Nikolaus Weiskopf, Patrik Vuilleumier, 2013, Neuroimage.

Estimating the transfer function from neuronal activity to BOLD using simultaneous EEG-fMRI

William D. Penny, James Kilner, Felix Blankenburg, 2010, NeuroImage.

Comparing Families of Dynamic Causal Models

Karl J. Friston, William D. Penny, Klaas E. Stephan, 2010, PLoS Comput. Biol..

Sparse network-based models for patient classification using fMRI

John Shawe-Taylor, Marta I. Garrido, Janaina Mourão Miranda, 2013, NeuroImage.

Embedding Anatomical or Functional Knowledge in Whole-Brain Multiple Kernel Learning Models

Janaina Mourão Miranda, Christophe Phillips, Maria J. Rosa, 2018, Neuroinformatics.

Multiple Holdouts With Stability: Improving the Generalizability of Machine Learning Analyses of Brain–Behavior Relationships

Michael Moutoussis, Gabriel Ziegler, Peter B. Jones, 2020, Biological Psychiatry.

Conditional Gaussian Graphical Models for Multi-output Regression of Neuroimaging Data

Andre F. Marquand, Maria Joao Rosa, Orla M. Doyle, 2013 .

Estimating multivariate similarity between neuroimaging datasets with sparse canonical correlation analysis: an application to perfusion imaging

Andre F. Marquand, Orla M. Doyle, Fernando Zelaya, 2015, Front. Neurosci..

Decoding the matrix: Benefits and limitations of applying machine learning algorithms to pain neuroimaging

Ben Seymour, Maria Joao Rosa, B. Seymour, 2014, PAIN®.

Pattern Recognition for Neuroimaging Toolbox

Christophe Phillips, Jonas Richiardi, John Ashburner, 2013 .

Full Bayesian multi-task learning for multi-output brain decoding and accommodating missing data

Andre F. Marquand, Steven C. R. Williams, Orla M. Doyle, 2014, 2014 International Workshop on Pattern Recognition in Neuroimaging.

Connectivity-based neurofeedback: Dynamic causal modeling for real-time fMRI☆

Sebastian W. Rieger, F. Scharnowski, D. Ville, 2013, NeuroImage.

Classification and characterisation of brain network changes in chronic back pain: A multicenter study [version 2; peer review: 3 approved]

B. Seymour, M. Kawato, W. Yoshida, 2022 .

Multiple hold-outs with stability: improving the generalizability of machine learning analyses of brain-behaviour relationships

Fabio S. Ferreira, M. Moutoussis, J. Mourão-Miranda, 2019 .