National Institute of Neurological Disorders and Stroke Common Data Element Project - approach and methods.

BACKGROUND: In neuroscience clinical research studies, much time and effort are devoted to deciding what data to collect and developing data collection forms and data management systems to capture the data. Many investigators receiving funding from National Institute of Neurological Disorders and Stroke (NINDS), the National Institutes of Health (NIH), are required to share their data once their studies are complete, but the multitude of data definitions and formats make it extremely difficult to aggregate data or perform meta-analyses across studies. PURPOSE: In an effort to assist investigators and accelerate data sharing in neuroscience clinical research, the NINDS has embarked upon the Common Data Element (CDE) Project. The data standards developed through the NINDS CDE Project enable clinical investigators to systematically collect data and should facilitate study start-up and data aggregation across the research community. METHODS: The NINDS CDE Team has taken a systematic, iterative approach to develop the critical core and the disease-specific CDEs. The CDE development process provides a mechanism for community involvement and buy-in, offers a structure for decision making, and includes a technical support team. RESULTS: Upon conclusion of the development process, the CDEs and accompanying tools are available on the Project Web site - http://www.commondataelements.ninds.nih.gov/. The Web site currently includes the critical core (aka general) CDEs that are applicable to all clinical research studies regardless of therapeutic area as well as several disease-specific CDEs. Additional disease-specific CDEs will be added to the Web site once they are developed and vetted over the next 12 months. LIMITATIONS: The CDEs will continue to evolve and will improve only if clinical researchers use and offer feedback about their experience with them. Thus, the NINDS program staff strongly encourages its clinical research grantees to use the CDEs and is expanding its efforts to educate the neuroscience research community about the CDEs and to train research teams to incorporate them into their studies. CONCLUSIONS: Version 1.0 of a set of CDEs has been published, but publication is not the end of the development process. All CDEs will be evaluated and revised at least annually to ensure that they reflect current clinical research practices in neuroscience.

Common data elements in epilepsy research: development and implementation of the NINDS epilepsy CDE project.

The Common Data Element (CDE) Project was initiated in 2006 by the National Institute of Neurological Disorders and Stroke (NINDS) to develop standards for performing funded neuroscience-related clinical research. CDEs are intended to standardize aspects of data collection; decrease study start-up time; and provide more complete, comprehensive, and equivalent data across studies within a particular disease area. Therefore, CDEs will simplify data sharing and data aggregation across NINDS-funded clinical research, and where appropriate, facilitate the development of evidenced-based guidelines and recommendations. Epilepsy-specific CDEs were established in nine content areas: (1) Antiepileptic Drugs (AEDs) and Other Antiepileptic Therapies (AETs), (2) Comorbidities, (3) Electrophysiology, (4) Imaging, (5) Neurological Exam, (6) Neuropsychology, (7) Quality of Life, (8) Seizures and Syndromes, and (9) Surgery and Pathology. CDEs were developed as a dynamic resource that will accommodate recommendations based on investigator use, new technologies, and research findings documenting emerging critical disease characteristics. The epilepsy-specific CDE initiative can be viewed as part of the larger international movement toward "harmonization" of clinical disease characterization and outcome assessment designed to promote communication and research efforts in epilepsy. It will also provide valuable guidance for CDE improvement during further development, refinement, and implementation. This article describes the NINDS CDE Initiative, the process used in developing Epilepsy CDEs, and the benefits of CDEs for the clinical investigator and NINDS.

What learning to see arbitrary motion tells us about biological motion perception.

In separate studies, observers viewed upright biological motion, inverted biological motion, or arbitrary motion created from systematically randomizing the positions of point-light dots. Results showed that observers (a) could learn to detect the presence of arbitrary motion, (b) could not learn to discriminate the coherence of arbitrary motion, although they could do so for upright biological motion, (c) could apply a detection strategy to learn to detect the presence of inverted biological motion nearly as well as they detected upright biological motion, and (d) performed better discriminating the coherence of upright biological motion compared with inverted biological motion. These results suggest that learning and form information play an important role in perceiving biological motion, although this role may only be apparent in tasks that require processing information from multiple parts of the motion display.

Temporal properties in masking biological motion.

The perception of biological motion using point light animation techniques was investigated in several experiments. Animations simulating walking were presented with additional masking dots. The temporal properties of the walking motion or the temporal relationship between the walking and masking motions were systematically manipulated. Results showed that (1) perception of biological motion was sensitive to even small temporal perturbation within the walker, (2) the effectiveness of a mask depended upon the temporal phase difference between the mask and point light walker, (3) relatively small temporal differences between the mask and point light walker decreased the effectiveness of the mask, and (4) these effects were not due simply to observers detecting the phase offsets in the display. Temporal properties of the motion are important in perceiving the human form in action, just as in other types of figure-ground segregation. This information may be processed by both motion and form pathways for processing biological motion.