Multivariate decoding methods were developed originally as tools to enable accurate
predictions in real-world applications. The realization that these methods can also be …

Over the past decade fMRI researchers have developed increasingly sensitive techniques
for analyzing the information represented in BOLD activity. The most popular of these …

The 21st century marks the emergence of “big data” with a rapid increase in the availability
of datasets with multiple measurements. In neuroscience, brain-imaging datasets are more …

A fundamental challenge for systems neuroscience is to quantitatively relate its three major
branches of research: brain-activity measurement, behavioral measurement, and …

Representational models specify how activity patterns in populations of neurons (or, more
generally, in multivariate brain-activity measurements) relate to sensory stimuli, motor …

It has become accepted in the neuroscience community that perception and performance
are quintessentially multisensory by nature. Using the full palette of modern brain imaging …

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Neuroscience is undergoing faster changes than ever before. Over 100 years our field
qualitatively described and invasively manipulated single or few organisms to gain …

A number of recent studies have begun to show the promise of magnetoencephalography
(MEG) as a means to non-invasively measure functional connectivity within distributed …

This paper describes an application of hierarchical or empirical Bayes to the distributed
source reconstruction problem in electro-and magnetoencephalography (EEG and MEG) …