There is a growing number of human brain imaging datasets shared online that have related metadata, such as demographic and phenotypic information. The 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data-sharing Initiative (INDI) are great examples of openly available brain imaging datasets with corresponding metadata. However, these data have diverse directory structures and file formats that make cross-dataset queries a time intensive project.

The MetaSearch App provides an integrated view of the many projects organized under the FCP and INDI efforts (summarized below). MetaSearch accomplishes this by extracting metadata for these projects from the AWS cloud, transforming it into a common data model, and the loading the integrated dataset into the MetaSearch app.

The MetaSearch app uses an implementation of parallel coordinate charts written in D3.js that allows for selecting subsets of multidimensional datasets that are also rendered in a tabular format using SlickGrid.

By using this app you can perform queries visually to select a cohort of participants with brain imaging data based on their demographics and phenotypic information and then link out to imaging measures. For example, you could select participants that are female between the ages of 20 to 30 with a Verbal IQ between 100 and 120.

Demo: https://openneurolab.github.io/metasearch

Please refer to and follow the data licenses and use agreements listed on the homepage of each of the datasets in the table below.