Contemporary research in neuroimaging and neuroscience depends heavily on technical quantitative expertise in the areas of study design, statistical modeling and inference, and computation. The inclusion of a Design and Analysis Core is motivated by the need to provide access to COBRE investigators, and the neuroimaging research community at Brown, to the diverse set of tools and expertise required to conduct work in this area. Having a core with faculty and staff from the fields of statistics, neuroscience and physics will obviate or minimize the need for COBRE project leaders to seek these resources on their own. The primary mission of the DAC will be collaboration with COBRE investigators on issues related to design, analysis, and computing. We will work with investigators on standard aspects of design and analysis, and provide access to technical staff needed for acquiring and formatting image data, using computer clusters, implementing data analyses on various software platforms, and archiving project data (including image data) on servers. Several projects will demand development of new methodology, and the faculty configuration of the core is designed to respond to those demands and indeed to generate synergy in methods development. The core will coordinate and facilitate access to computational resources available to investigators. These resources include hardware (e.g., computing clusters, data archiving platforms), software (specialized programs such as AFNI, SPM, Brain Voyager;more general tools such as Matlab and R, and tools developed at Brown for visualization and analysis), and technical personnel with expertise in programming and software operation. The core will organize a regular working group and seminar series, providing a venue for the active exchange of ideas on design, statistical analysis and methodology, computation, software, and related issues between neuroimaging researchers both within and outside of Brown.

Public Health Relevance

Contemporary neuroscience research requires synthesis and integration of information drawn from brain images, characteristics of genomic sequences, and phenotypic measure, accomplished by using mathematical and statistical models implemented on high-end computing systems. This core provides expertise and infrastructure needed to meet the complex analytic requirements of each research project.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Exploratory Grants (P20)
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Special Emphasis Panel (ZGM1-TWD-B)
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Brown University
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Song, Joo-Hyun; B├ędard, Patrick (2015) Paradoxical benefits of dual-task contexts for visuomotor memory. Psychol Sci 26:148-58
Moher, Jeff; Sit, Jonathan; Song, Joo-Hyun (2015) Goal-directed action is automatically biased towards looming motion. Vision Res 113:188-97
Aguiar, Derek; Wong, Wendy S W; Istrail, Sorin (2014) Tumor haplotype assembly algorithms for cancer genomics. Pac Symp Biocomput :3-14
Amso, Dima; Haas, Sara; Markant, Julie (2014) An eye tracking investigation of developmental change in bottom-up attention orienting to faces in cluttered natural scenes. PLoS One 9:e85701
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Schlesinger, Matthew; Johnson, Scott P; Amso, Dima (2014) Prediction-learning in infants as a mechanism for gaze control during object exploration. Front Psychol 5:441
Moher, Jeff; Song, Joo-Hyun (2014) Perceptual decision processes flexibly adapt to avoid change-of-mind motor costs. J Vis 14:1
Amso, Dima; Haas, Sara; Tenenbaum, Elena et al. (2014) Bottom-up attention orienting in young children with autism. J Autism Dev Disord 44:664-73
Corbett, Jennifer E; Song, Joo-Hyun (2014) Statistical extraction affects visually guided action. Vis cogn 22:881-895
McLean, Rebecca L; Johnson Harrison, Ashley; Zimak, Eric et al. (2014) Executive function in probands with autism with average IQ and their unaffected first-degree relatives. J Am Acad Child Adolesc Psychiatry 53:1001-9

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