UCLA Multimodal Connectivity Database

The UCLA Multimodal Connectivity Database (UMCD) is a web-based repository and analysis site for connectivity matrices that have been derived from de-identified neuroimaging data. Users can analyze connectivity matrices that have been shared publicly and upload their own matrices to share or analyze privately.

Analyze a Brain Network

To analyze any shared brain network, choose a study name, a network name from that study, a weighting scheme, and the percentage of edges to include, then click Analyze. Momentarily, you'll get a full breakdown of the chosen network, including study info and network analysis.

Study Name:	UCLA ADHD_child1000_Functional_ConnectomesADHD200ADHD_200RPMNKI_RocklandADHD200_CC200UCLA_CCN_APOE_DTIICBMUCLA_Autism	Choose from the list of available studies
Network Name:		Choose from the list of shared networks for the chosen study
Weighting scheme::	BinaryWeighted	Choose a weighting scheme for the network, either weighted or binarized edges
% of edges to include::		Choose the percent of connections to keep (0-100%)
Orientation:	AxialSagittalCoronal	Choose the orientation from which to view the network