English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Model-based feature construction for multivariate decoding

Brodersen, K. H., Haiss, F., Ong, C. S., Jung, F., Tittgemeyer, M., Buhmann, J. M., et al. (2011). Model-based feature construction for multivariate decoding. NeuroImage, 56(2), 601-615. doi:10.1016/j.neuroimage.2010.04.036.

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Brodersen, Kay H.1, Author
Haiss, Florent1, Author
Ong, Cheng Song1, Author
Jung, Fabienne2, Author           
Tittgemeyer, Marc3, Author           
Buhmann, Joachim M.1, Author
Weber, Bernd1, Author
Stephan, Klaas Enno4, Author           
Affiliations:
1a Department of Computer Science, ETH Zurich, Switzerland b Laboratory for Social and Neural Systems Research, Institute for Empirical Research in Economics, University of Zurich, Switzerland c Institute of Pharmacology and Toxicology, University of Zurich, Switzerland d Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom, ou_persistent22              
2Translational Neurocircuitry, Research Groups, Max Planck Institute for Metabolism Research, Managing Director: Jens Brüning, Max Planck Society, ou_2149668              
3Tittgemeyer – Translational Neurocircuitry, Research Groups, Max Planck Institute for Metabolism Research, Max Planck Society, ou_2149668              
4Stephan – Translational Neuromodelling, External Scientific Members, Max Planck Institute for Metabolism Research, Max Planck Society, ou_3485601              

Content

show
hide
Free keywords: -
 Abstract: © 2010 Elsevier Inc.

Details

show
hide
Language(s): eng - English
 Dates: 2011
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: eDoc: 477034
DOI: 10.1016/j.neuroimage.2010.04.036
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: NeuroImage
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 56 (2) Sequence Number: - Start / End Page: 601 - 615 Identifier: ISSN: 10538119