TY - JOUR
AU - 
AB - METHODS ARTICLE published: 28 November 2012 NEUROINFORMATICS doi: 10.3389/fninf.2012.00028 The UCLA multimodal connectivity database: a web-based platform for brain connectivity matrix sharing and analysis 1,2,3 3,4 5 6 Jesse A. Brown *, Jeffrey D. Rudie , Anita Bandrowski , John D. Van Horn * and 1,2 Susan Y. Bookheimer Center for Cognitive Neuroscience, University of California Los Angeles, Los Angeles, CA, USA Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA Interdepartmental Program in Neuroscience, University of California Los Angeles, Los Angeles, CA, USA Brain Mapping Center, University of California Los Angeles, Los Angeles, CA, USA Center for Research in Biological Systems, University of California San Diego, San Diego, CA, USA Laboratory of Neuroimaging, Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA Edited by: Brain connectomics research has rapidly expanded using functional MRI (fMRI) and Marc-Oliver Gewaltig, Ecole diffusion-weighted MRI (dwMRI). A common product of these varied analyses is a Polytechnique Fédérale de connectivity matrix (CM). A CM stores the connection strength between any two Lausanne, Switzerland regions (“nodes”) in a brain network. This format is useful for several reasons: Reviewed by: (1) it is highly distilled, with minimal 
TI - The UCLA multimodal connectivity database: a web-based platform for brain connectivity matrix sharing and analysis
JF - Frontiers in Neuroinformatics
DO - 10.3389/fninf.2012.00028
DA - 2012-01-01
UR - https://www.deepdyve.com/lp/unpaywall/the-ucla-multimodal-connectivity-database-a-web-based-platform-for-eDkrau9hKG
DP - DeepDyve
ER -