PRNI Programme


Sessions


  • Session 1: regularisation and regression
    • A Linear Gaussian Framework for Decoding of Perceived Images (Marcel A.J. van Gerven and Tom Heskes)
    • Improved brain pattern recovery through ranking approaches (Fabian Pedregosa, Elodie Cauvet, Gaël Varoquaux, Christophe Pallier, Bertrand Thirion, and Alexandre Gramfort)
    • Structured Sparsity Models for Brain Decoding from fMRI data (Luca Baldassarre, Janaina Mourao-Miranda, and Massimiliano Pontil)
    • Decoding Visual Percepts Induced by Word Reading with fMRI (Alexandre Gramfort, Christophe Pallier, Gaël Varoquaux, and Bertrand Thirion)
  • Session 2: projections, decompositions & transforms
    • Towards identification and characterisation of selective fMRI feature sets using Independent Component Analysis (Loizos Markides and Duncan Fyfe Gillies)
    • ICA component selection based on sparse activelet reconstruction for fMRI analysis in refractory focal epilepsy (Borbala Hunyadi, Bogdan Mijovic, Simon Tousseyn, Patrick Dupont, Wim Van Paesschen, Sabine Van Huffel, and Maarten De Vos)
    • Inter-brain mutual Information in Social Interaction tasks (Muhammad Naeem, T.M. Mcginnity, David Watson, Kongfatt Wong-Lin, Girijesh Prasad, and J.A. Scott Kelso)
    • Joint Sparse Representation of Brain Activity Patterns related to Perceptual and Cognitive Components of a Speech Comprehension Task (Mahdi Ramezani, Purang Abolmaesumi, Kris Marble, H. Macdonald, and Ingrid Johnsrude)
    • Multivariate fMRI Analysis using Optimally-Discriminative Voxel-Based Analysis (Tianhao Zhang, Theodore D. Satterthwaite, Mark Elliott, Ruben C. Gur, Raquel E. Gur, and Christos Davatzikos)
    • Multilayer Scattering Image Analysis Fits fMRI Activity in Visual Areas (Michael Eickenberg, Alexandre Gramfort, and Bertrand Thirion)
  • Session 3: dimensionality reduction & feature selection
    • Feature-Space Quantization for Data-Driven Search (Nergis Tomen, Makoto Takemiya, Takeshi Matsuo, Isao Hasegawa, and Yukiyasu Kamitani)
    • Parameter Selection in Mutual Information-Based Feature Selection in Automated Diagnosis of Multiple Epilepsies Using Scalp EEG (Wesley T. Kerr, Ariana Anderson, Hongjing Xia, Eric S. Braun, Edward P. Lau, Andrew Y. Cho, and Mark S. Cohen)
    • Voxel selection in MRI through bagging and conformal analysis: Application to detection of Obsessive Compulsive Disorder (Emilio Parrado-Hernandez, Vanessa Gómez-Verdejo, Manel Martínez-Ramón, John Shawe-Taylor, P. Alonso, J. Pujol, J.M. Menchon, N. Cardoner, and Carles Soriano-Mas)
    • On spatial selectivity and prediction across conditions with fMRI (Yannick Schwartz, Gaël Varoquaux, and Bertrand Thirion)
  • Session 4: multiclass problems & methods
    • Testing Multiclass Pattern Discrimination (Emanuele Olivetti, Susanne Greiner, and Paolo Avesani)
    • Decoding spontaneous brain activity from fMRI using Gaussian Processes: tracking brain reactivation (Jessica Schrouff, Caroline Kussé, Louis Wehenkel, Pierre Maquet, and Christophe Phillips)
    • Classification and Visualization of Multiclass fMRI Data Using Supervised Self-Organizing Maps (Lars Haufeld, Roberta Santoro, Giancarlo Valente, and Elia Formisano)
  • Session 5: connectivity, graphs & networks
    • Statistical kernel-based modeling of connectomes (Félix Renard, Christian Heinrich, Sophie Achard, Edouard Hirsch, and Stéphane Kremer)
    • Sparse dictionary learning of resting state fMRI networks (Harini Eavani, Roman Filipovych, Christos Davatzikos, Theodore D. Satterthwaite, Raquel E. Gur, and Ruben C. Gur)
    • Automatic Tractography Analysis through Sparse Networks in Case-Control Studies (Luca Giancardo, Diego Sona, Alessadro Gozzi, Angelo Bifone, Vittorio Murino, Sara Migliarini, Giulia Pacini, Barbara Pelosi, and Massimo Pasqualetti)
    • Addressing Missing Nodes as Missing Data in Dynamic Causal Modeling (Christopher L. Wyatt and Shaza B. Zaghlool)
    • The Approximation of the Dissimilarity Projection (Emanuele Olivetti, Thien Bao Nguyen, and Eleftherios Garyfallidis)
  • Session 6: ensembling & multimodality
    • Biomarker evaluation by Multiple Kernel Learning for Schizophrenia detection (Aydin Ulas, Umberto Castellani, Vittorio Murino, Marcella Bellani, Michele Tansella, and Paolo Brambilla)
    • Discrimination of Discrete Feedback During Performance of Motor Imagery (Matthew Dyson, Laurence Casini, and Boris Burle)
    • Spatiotemporal Searchlight Representational Similarity Analysis in EMEG Source Space (Li Su, Elisabeth Fonteneau, William Marslen-Wilson, and Nikolaus Kriegeskorte)
    • Connectivity-informed Sparse Classifiers for fMRI Brain Decoding (Bernard Ng, Viviana Siless, Gaël Varoquaux, Jean-Baptiste Poline, Bertrand Thirion, and Rafeef Abugharbieh)
    • A composite multivariate polygenic and neuroimaging score for prediction of conversion to Alzheimer's disease (Roman Filipovych, Bilwaj Gaonkar, and Christos Davatzikos)