The Human Connectome Project (HCP) has developed protocols, standard operating and quality control procedures, and a suite of informatics tools to enable high throughput data collection, data sharing, automated data processing and analysis, and data mining and visualization. Quality control procedures include methods to maintain data collection consistency over time, to measure head motion, and to establish quantitative modality-specific overall quality assessments. Database services developed as customizations of the XNAT imaging informatics platform support both internal daily operations and open access data sharing. The Connectome Workbench visualization environment enables user interaction with HCP data and is increasingly integrated with the HCP's database services. Here we describe the current state of these procedures and tools and their application in the ongoing HCP study.

Exposure to trauma in childhood or adolescence has been shown to be associated with a variety of deleterious mental health outcomes including, psychotic experiences, 1,2 depression, 3 bipolar disorder 4 and psychosis. 5 Specifically, metaanalyses have shown that those exposed to any form of childhood maltreatment are much more likely to report

ConnectomeDB is a database for housing and disseminating data about human brain structure, function, and connectivity, along with associated behavioral and demographic data. It is the main archive and dissemination platform for data collected under the WU-Minn consortium Human Connectome Project. Additional connectome-style study data is and will be made available in the database under current and future projects, including the Connectome Coordination Facility. The database currently includes multiple modalities of magnetic resonance imaging (MRI) and magnetoencephalograpy (MEG) data along with associated behavioral data. MRI modalities include structural, task, resting state and diffusion. MEG modalities include resting state and task. Imaging data includes unprocessed, minimally preprocessed and analysis data. Imaging data and much of the behavioral data are publicly available, subject to acceptance of data use terms, while access to some sensitive behavioral data is restricted to qualified investigators under a more stringent set of terms. ConnectomeDB is the public side of the WU-Minn HCP database platform. As such, it is geared towards public distribution, with a web-based user interface designed to guide users to the optimal set of data for their needs and a robust backend mechanism based on the commercial Aspera fasp service to enable high speed downloads. HCP data is also available via direct shipment of hard drives and Amazon S3.

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Despite its long-standing and widespread use, disagreement remains regarding the structure of the Rosenberg Self-Esteem Scale (RSES). In particular, concern remains regarding the degree to which the scale assesses self-esteem as a unidimensional or multidimensional (positive and negative self-esteem) construct. Using a sample of 3,862 high school students in the United Kingdom, 4 models were tested: (a) a unidimensional model, (b) a correlated 2-factor model in which the 2 latent variables are represented by positive and negative self-esteem, (c) a hierarchical model, and (d) a bifactor model. The totality of results including item loadings, goodness-of-fit indexes, reliability estimates, and correlations with self-efficacy measures all supported the bifactor model, suggesting that the 2 hypothesized factors are better understood as "grouping" factors rather than as representative of latent constructs. Accordingly, this study supports the unidimensionality of the RSES and the scoring of all 10 items to produce a global self-esteem score.