The nature of mental illness remains a conundrum. Traditional disease categories are
increasingly suspected to misrepresent the causes underlying mental disturbance. Yet …

Multivariate pattern analysis (MVPA) or brain decoding methods have become standard
practice in analyzing fMRI data. Although decoding methods have been extensively applied …

The human brain achieves visual object recognition through multiple stages of linear and
nonlinear transformations operating at a millisecond scale. To predict and explain these …

Statistical machine learning methods are increasingly used for neuroimaging data analysis.
Their main virtue is their ability to model high-dimensional datasets, eg, multivariate analysis …

Cortical regions apparently selective to faces, places, and bodies have provided important
evidence for domain-specific theories of human cognition, development, and evolution. But …

Neuronal population codes are increasingly being investigated with multivariate pattern-
information analyses. A key challenge is to use measured brain-activity patterns to test …

MVPA-Light is a MATLAB toolbox for multivariate pattern analysis (MVPA). It provides native
implementations of a range of classifiers and regression models, using modern optimization …

The cognitive concept of representation plays a key role in theories of brain information
processing. However, linking neuronal activity to representational content and cognitive …

Chronic pain is the greatest source of disability globally and claims related to chronic pain
feature in many insurance and medico-legal cases. Brain imaging (for example, functional …

Human fMRI signals exhibit a spatial patterning that contains detailed information about a
person's mental states. Using classifiers it is possible to access this information and study …