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ORCID24. NIPS 2011: Sierra Nevada, Spain - MLINI
- Georg Langs, Irina Rish, Moritz Grosse-Wentrup, Brian Murphy:
Machine Learning and Interpretation in Neuroimaging - International Workshop, MLINI 2011, Held at NIPS 2011, Sierra Nevada, Spain, December 16-17, 2011, Revised Selected and Invited Contributions. Lecture Notes in Computer Science 7263, Springer 2012, ISBN 978-3-642-34712-2
Coding and Decoding
- Vincent Michel, Alexandre Gramfort
, Evelyn Eger, Gaël Varoquaux, Bertrand Thirion:
A Comparative Study of Algorithms for Intra- and Inter-subjects fMRI Decoding. 1-8 - Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion:
Beyond Brain Reading: Randomized Sparsity and Clustering to Simultaneously Predict and Identify. 9-16 - Shahar Jamshy, Omri Perez, Yehezkel Yeshurun, Talma Hendler, Nathan Intrator:
Searchlight Based Feature Extraction. 17-25 - Joset A. Etzel, Michael W. Cole, Todd S. Braver:
Looking Outside the Searchlight. 26-33 - Michael A. Casey, Jessica Thompson, Olivia Kang, Rajeev D. S. Raizada, Thalia Wheatley:
Population Codes Representing Musical Timbre for High-Level fMRI Categorization of Music Genres. 34-41 - Emanuele Olivetti, Susanne Greiner, Paolo Avesani:
Induction in Neuroscience with Classification: Issues and Solutions. 42-50 - Jane M. Rondina, John Shawe-Taylor, Janaina Mourão Miranda:
A New Feature Selection Method Based on Stability Theory - Exploring Parameters Space to Evaluate Classification Accuracy in Neuroimaging Data. 51-59 - Emilio Parrado-Hernández, Vanessa Gómez-Verdejo, Manel Martínez-Ramón, Pino Alonso, Jesús Pujol, José Manuel Menchón, Narcís Cardoner, Carles Soriano-Mas:
Identification of OCD-Relevant Brain Areas through Multivariate Feature Selection. 60-67 - George H. Chen, Evelina Fedorenko, Nancy Kanwisher, Polina Golland:
Deformation-Invariant Sparse Coding for Modeling Spatial Variability of Functional Patterns in the Brain. 68-75 - Toke Jansen Hansen, Lars Kai Hansen, Kristoffer Hougaard Madsen:
Decoding Complex Cognitive States Online by Manifold Regularization in Real-Time fMRI. 76-83
Neuroscience
- David B. Keator:
Modality Neutral Techniques for Brain Image Understanding. 84-92 - Pavan Ramkumar, Sebastian Pannasch, Bruce C. Hansen, Adam M. Larson, Lester C. Loschky:
How Does the Brain Represent Visual Scenes? A Neuromagnetic Scene Categorization Study. 93-100 - Miika Koskinen:
Finding Consistencies in MEG Responses to Repeated Natural Speech. 101-107 - Sivan Kinreich, Ilana Podlipsky, Nathan Intrator, Talma Hendler:
Categorized EEG Neurofeedback Performance Unveils Simultaneous fMRI Deep Brain Activation. 108-115 - Philip P. Kwok, Olga Ciccarelli, Declan T. Chard, David H. Miller, Daniel C. Alexander:
Predicting Clinically Definite Multiple Sclerosis from Onset Using SVM. 116-123 - Chris Hinrichs, N. Maritza Dowling, Sterling C. Johnson, Vikas Singh:
MKL-Based Sample Enrichment and Customized Outcomes Enable Smaller AD Clinical Trials. 124-131 - Diego Sona, Paolo Avesani, Stefano Magon, Gianpaolo Basso, Gabriele Miceli:
Pairwise Analysis for Longitudinal fMRI Studies. 132-139
Dynamics
- Felix Bießmann, Yusuke Murayama, Nikos K. Logothetis, Klaus-Robert Müller, Frank C. Meinecke:
Non-separable Spatiotemporal Brain Hemodynamics Contain Neural Information. 140-147 - Ali Bahramisharif, Marcel A. J. van Gerven, Jan-Mathijs Schoffelen, Zoubin Ghahramani, Tom Heskes:
The Dynamic Beamformer. 148-155 - Hans J. P. Wouters, Marcel A. J. van Gerven, Matthias Sebastian Treder, Tom Heskes, Ali Bahramisharif:
Covert Attention as a Paradigm for Subject-Independent Brain-Computer Interfacing. 156-163 - Maxime Cauchoix, Ali Bilgin Arslan, Denis Fize, Thomas Serre:
The Neural Dynamics of Visual Processing in Monkey Extrastriate Cortex: A Comparison between Univariate and Multivariate Techniques. 164-171 - Gaël Varoquaux, Bertrand Thirion:
Statistical Learning for Resting-State fMRI: Successes and Challenges. 172-177 - Fani Deligianni, Gaël Varoquaux, Bertrand Thirion, Emma C. Robinson, David J. Sharp, A. David Edwards, Daniel Rueckert:
Relating Brain Functional Connectivity to Anatomical Connections: Model Selection. 178-185 - Nico S. Gorbach, Silvan Siep, Jenia Jitsev, Corina Melzer, Marc Tittgemeyer:
Information-Theoretic Connectivity-Based Cortex Parcellation. 186-193 - Justin Dauwels, Hang Yu, Xueou Wang, François B. Vialatte, Charles-François Vincent Latchoumane, Jaeseung Jeong, Andrzej Cichocki:
Inferring Brain Networks through Graphical Models with Hidden Variables. 194-201 - Stefan Haufe, Vadim V. Nikulin, Guido Nolte, Klaus-Robert Müller:
Pitfalls in EEG-Based Brain Effective Connectivity Analysis. 202-209
Probabilistic Models and Machine Learning
- Orla M. Doyle, Mitul A. Mehta, Michael J. Brammer, Adam J. Schwarz, Sara De Simoni, Andre F. Marquand:
Data-Driven Modeling of BOLD Drug Response Curves Using Gaussian Process Learning. 210-217 - Evangelos Roussos, Steven Roberts, Ingrid Daubechies:
Variational Bayesian Learning of Sparse Representations and Its Application in Functional Neuroimaging. 218-225 - Kasper Winther Andersen, Kristoffer Hougaard Madsen, Hartwig R. Siebner, Lars Kai Hansen, Morten Mørup:
Identification of Functional Clusters in the Striatum Using Infinite Relational Modeling. 226-233 - Kai-min Kevin Chang, Brian Murphy, Marcel Adam Just:
A Latent Feature Analysis of the Neural Representation of Conceptual Knowledge. 234-241 - Ariana E. Anderson, Dianna Han, Pamela K. Douglas, Jennifer E. Bramen, Mark S. Cohen:
Real-Time Functional MRI Classification of Brain States Using Markov-SVM Hybrid Models: Peering Inside the rt-fMRI Black Box. 242-255 - Trine Julie Abrahamsen, Lars Kai Hansen:
Restoring the Generalizability of SVM Based Decoding in High Dimensional Neuroimage Data. 256-263
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