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Publicly Available Published by De Gruyter February 25, 2017

Multivariate decoding of fMRI data

Towards a content-based cognitive neuroscience

J. Heinzle, S. Anders, S. Bode, C. Bogler, Y. Chen, R.M. Cichy, K. Hackmack, T. Kahnt, C. Kalberlah, C. Reverberi, C.S. Soon, A. Tusche, M. Weygandt and J.-D. Haynes
From the journal e-Neuroforum

Abstract

The advent of functional magnetic resonance imaging (fMRI) of brain function 20 years ago has provided a new methodology for non-in­vasive measurement of brain function that is now widely used in cognitive neurosci­ence. Traditionally, fMRI data has been an­alyzed looking for overall activity chang­es in brain regions in response to a stimu­lus or a cognitive task. Now, recent develop­ments have introduced more elaborate, con­tent-based analysis techniques. When mul­tivariate decoding is applied to the detailed patterning of regionally-specific fMRI signals, it can be used to assess the amount of infor­mation these encode about specific task-vari­ables. Here we provide an overview of sev­eral developments, spanning from applica­tions in cognitive neuroscience (perception, attention, reward, decision making, emotion­al communication) to methodology (informa­tion flow, surface-based searchlight decod­ing) and medical diagnostics.

Published Online: 2017-2-25
Published in Print: 2012-3-1

© 2017 by Walter de Gruyter Berlin/Boston

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