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

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

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

Representational similarity analysis (RSA) is a multivariate method that can be used to
extract information about distributed patterns of representations across the brain. It is related …

Perceptual and cognitive content is thought to be represented in the brain by patterns of
activity across populations of neurons. In order to test whether a computational model can …

Studies of the primate visual system have begun to test a wide range of complex
computational object-vision models. Realistic models have many parameters, which in …

In recent years there has been growing interest in multivariate analyses of neuroimaging
data, which can be used to detect distributed patterns of activity that encode an experimental …

Representational similarity analysis (RSA) is a computational technique that uses pairwise
comparisons of stimuli to reveal their representation in higher-order space. In the context of …

Convolutional neural networks (CNNs) are increasingly used to model human vision due to
their high object categorization capabilities and general correspondence with human brain …

Representational similarity analysis of activation patterns has become an increasingly
important tool for studying brain representations. The dissimilarity between two patterns is …