Machine Learning and Interpretation in Neuroimaging

A Comparative Study of Algorithms for Intra- and Inter-subjects fMRI Decoding.- Beyond Brain Reading: Randomized Sparsity and Clustering to Simultaneously Predict and Identify.- Searchlight Based Feature Extraction.- Looking Outside the Searchlight.- Population Codes Representing Musical Timbre for High-Level fMRI Categorization of Music Genres.- Induction in Neuroscience with Classification: Issues and Solutions.- A New Feature Selection Method Based on Stability Theory - Exploring Parameters Space to Evaluate Classification Accuracy in Neuroimaging Data.- Identification of OCD-Relevant Brain Areas through Multivariate Feature Selection.- Deformation-Invariant Sparse Coding for Modeling Spatial Variability of Functional Patterns in the Brain.- Decoding Complex Cognitive States Online by Manifold Regularization in Real-Time fMRI.- Modality Neutral Techniques for Brain Image Understanding.- How Does the Brain Represent Visual Scenes? A Neuromagnetic Scene Categorization Study.- Finding Consistencies in MEG Responses to Repeated Natural Speech.- Categorized EEG Neurofeedback Performance Unveils Simultaneous fMRI Deep Brain Activation.- Predicting Clinically Definite Multiple Sclerosis from Onset Using SVM.- MKL-Based Sample Enrichment and Customized Outcomes Enable Smaller AD Clinical Trials.- Pairwise Analysis for Longitudinal fMRI Studies.- Non-separable Spatiotemporal Brain Hemodynamics Contain Neural Information.- The Dynamic Beamformer.- Covert Attention as a Paradigm for Subject-Independent Brain-Computer Interfacing.- The Neural Dynamics of Visual Processing in Monkey Extrastriate Cortex: A Comparison between Univariate and Multivariate Techniques.- Statistical Learning for Resting-State fMRI: Successes and Challenges.- Relating Brain Functional Connectivity to Anatomical Connections: Model Selection.- Information-Theoretic Connectivity-Based Cortex Parcellation.- Inferring Brain Networks through Graphical Models with Hidden Variables.- Pitfalls in