Suchergebnisse

Data sharing is becoming increasingly common, but despite encouragement and facilitation by funding agencies, journals, and some research efforts, most neuroimaging data acquired today is still not shared due to political, financial, social, and technical barriers to sharing data that remain. In particular, technical solutions are few for researchers that are not a part of larger efforts with dedicated sharing infrastructures, and social barriers such as the time commitment required to share can keep data from becoming publicly available. We present a system for sharing neuroimaging data, designed to be simple to use and to provide benefit to the data provider. The system consists of a server at the International Neuroinformatics Coordinating Facility (INCF) and user tools for uploading data to the server. The primary design principle for the user tools is ease of use: the user identifies a directory containing Digital Imaging and Communications in Medicine (DICOM) data, provides their INCF Portal authentication, and provides identifiers for the subject and imaging session. The user tool anonymizes the data and sends it to the server. The server then runs quality control routines on the data, and the data and the quality control reports are made public. The user retains control of the data and may change the sharing policy as they need. The result is that in a few minutes of the user's time, DICOM data can be anonymized and made publicly available, and an initial quality control assessment can be performed on the data. The system is currently functional, and user tools and access to the public image database are available at http://xnat.incf.org/.

AbstractMagnetic resonance imaging has undergone dramatic development in the past years. This has been paralleled by developments in the tools for extracting quantitative information from these images in support of capturing the anatomic features of brain development in living humans. This has revolutionized our expectations for current and future diagnostic and investigative work with the developing brain. This paper will cover the classes of information that are readily available in the MR image, the mechanisms for extracting quantitative results, and a sample of the application of these types of methods to developmental issues. These applications highlight tissue‐ and anatomic‐based contrasts in the nature and rate of developmental maturation within the brain. This will be followed by a discussion of the emergent themes of developmental science as elucidated by these classes of observation.

Abstract Developmental language disorder (DLD) is predominantly a language disorder, but children with DLD also manifest non‐language impairments, and neuroanatomical abnormalities have been found in multiple areas of the brain, not all language‐associated. We therefore performed a whole brain general segmentation analysis of all major brain regions on MRI scans of 24 DLD subjects (16M, 8F) and 30 controls (15M, 15F), ages 5.7 to 11.3 years. Children with DLD showed increased total brain volume, driven predominantly by a substantial increase in the volume of cerebral white matter. Cerebral cortex and caudate were relatively but not absolutely smaller in DLD. These findings are discussed in relation to issues of specificity vs. generality as they arise in debates about (1) modular vs. general processing deficits and connectionist modeling in DLD, (2) language‐specific vs. pervasive, non‐specific deficits in DLD and (3) specificity of the disorder vs. overlap with other disorders, notably autism.