Titlebook: Machine Learning and Interpretation in Neuroimaging; International Worksh Georg Langs,Irina Rish,Brian Murphy Conference proceedings 2012 S

競選運動

Beyond Brain Reading: Randomized Sparsity and Clustering to Simultaneously Predict and Identifyd to be consistent for support recovery. To account for the spatial correlations between voxels, our approach makes use of a spatially constrained hierarchical clustering algorithm. Results are provided on simulations and a visual experiment.

champaign

Induction in Neuroscience with Classification: Issues and Solutionsim that the current approaches to this hypothesis testing problem are suboptimal, do not cover all useful settings, and that they could lead to wrong conclusions. We present a more accurate statistical test and provide examples of its superiority.

清楚說話

Finding Consistencies in MEG Responses to Repeated Natural Speechian). These statistically significant correlations between test trial projections suggest that the proposed method can extract perception-related time series from long-lasting MEG responses to natural speech.

陰險

TOM

Pairwise Analysis for Longitudinal fMRI Studiesh. We illustrate the empirical results on a dataset concerned with a study on aphasia rehabilitation. The pairwise method allows to reproduce the same brain areas obtained with a reference approach based on GLM analysis. In addition the proposed method highlights new brain regions that are compliant with a neuroscientific interpretation.

Adornment

流動性

Conference proceedings 2012tatistics, computer science, neuroscience, biology, and engineering. Thus, methodological and technological advances that enable us to obtain measurements, examine relationships across observations, and link these data to neuroscientific hypotheses happen in a highly interdisciplinary environment. T

fiction

overhaul

Looking Outside the Searchlight information is present at all spatial scales, and its susceptibility to overfitting. These problems are demonstrated in a dataset in which, contrary to common expectation, voxels identified as informative do not clearly contain more information than those not so identified.

maverick

A New Feature Selection Method Based on Stability Theory – Exploring Parameters Space to Evaluate Clmprove the classification accuracy in relation to the wholebrain in different functional datasets; we evaluate the parameters influence in the results, getting some insight in reasonable ranges of values; and we show that combinations of parameters that yield the best accuracies are stable (i.e., they have low rates of false positive selections).