Scientific and Statistical Computing Core

科学与统计计算核心

• 批准号: 8940165
• 负责人: Robert Cox
• 金额: $ 134.88万
• 依托单位: NATIONAL INSTITUTE OF MENTAL HEALTH
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8940165
• 关键词: African; Age; Algorithms; Anxiety Disorders; Atlases; Basic Science; Brain; Brain Mapping; Brain imaging; Brain region; Cancer Patient; Childhood; Clinical; Collaborations; Complex; Computer Systems; Computer software; Computers; Connecticut; Consult; Consultations; Core Facility; Data; Data Analyses; Data Quality; Data Set; Deep Brain Stimulation; Development; Development Plans; Diffusion; Disease; Drug Addiction; Drug abuse; Educational process of instructing; Electrodes; Ensure; Epilepsy; Excision; Experimental Designs; Extramural Activities; Feedback; Florida; Functional Magnetic Resonance Imaging; Future; Gadolinium DTPA; Gene Expression; Genetic; Goals; Hour; Human; Human Activities; Image; Image Analysis; Imagery; Imaging technology; Individual; Institutes; Institution; Internet; Italy; Linux; Location; MRI Scans; Macaca; Magnetic Resonance Imaging; Malignant neoplasm of brain; Maps; Methodology; Methods; Mission; Mood Disorders; Morphologic artifacts; Motion; National Institute of Drug Abuse; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; Neurosurgeon; Online Systems; Operative Surgical Procedures; Output; Paper; Patients; Persons; Population; Positron-Emission Tomography; Process; Psyche structure; Public Health; Publications; Quality Control; Reporting; Research; Research Personnel; Research Project Grants; Resources; Rest; Romania; Sampling; Scanning; Site; Slide; Software Tools; Solutions; Source Code; Statistical Computing; Statistical Methods; Students; Subject Headings; Techniques; Time Series Analysis; United States National Institutes of Health; Universities; Update; Vision; Visual Cortex; Work; animal data; autism spectrum disorder; base; coral; design; human data; improved; interest; mathematical sciences; meetings; nervous system disorder; open source; programs; receptive field; research study; response; scientific computing; software development; tool; tumor; web site; white matter

The main mission of the Core is to help NIH researchers with analyses of their functional MRI (brain activation mapping) data. Along the way, we also help non-NIH investigators, mostly in the US but also some abroad. Several levels of help are provided, from short-term immediate aid to long-term development and planning. Consultations: The shortest term help comprises in-person consultations with investigators about issues that arise in their research. The issues that come up are quite varied, since there are many steps in carrying out FMRI data analyses and there are many different types of experiments. Common problems include: - How to set up experimental design so that data can be analyzed effectively? - Interpretation and correction of MRI imaging artifacts (a common one: subject head motion during scanning). - How to set up time series analysis to extract brain activation effects of interest, and to suppress non-activation artifacts? - Why don't AFNI results agree with SPM/FSL/something else? - How to analyze data to reveal connections between brain regions during certain mental tasks, or at rest? - How to carry out inter-patient (group) statistical analysis, especially when non-MRI data (e.g., genetic information, age, disease rating) needs to be incorporated? - How to get good registration between the functional results and the anatomical reference images, and between the brain images from different subjects? - What sequence of programs is "best" for analyzing a particular kind of data? - And, of course, reports of real or imagined bugs in the AFNI software, as well as feature requests (small, large, and extravagant). There are familiar themes in many of these consultations, but each meeting and each experiment raises unique questions and usually requires digging into the goals and details of the research project in order to ensure that nothing central is being overlooked. Complex statistical issues are often raised. Often, software needs to be developed or modified to help researchers answer their specific questions. Helping with the Methods sections of papers is often part of our duties, as well. Educational Efforts: The Core has developed (and updates) a 40-hour course on how to design and analyze FMRI data. This course is taught in a 5-day hands-on "bootcamp", and was taught thrice at the NIH during FY 2014 to a total of over 200 students. All material for this continually evolving course (software, sample data, scripts, and PowerPoint/PDF slides) are freely available on our Web site http://afni.nimh.nih.gov . The course material includes several sample datasets that are used to illustrate the entire process, starting with images output by MRI scanners and continuing through to the collective statistical analysis of groups of subjects. We also taught versions of this course at 4 non-NIH sites (the expenses for these trips were covered by the host universities): Cluj-Napoca (Romania), Coral Gables (Florida), Pisa (Italy), and New Haven (Connecticut). Algorithm and Software Development: The longest term support consists of developing new methods and software for FMRI data analysis, both to solve current problems and in anticipation of new needs. All of our software is incorporated into the AFNI package, which is Unix/Linux/Macintosh-based open-source and is available for download by anyone in source code or binary formats. New programs are created, and old programs modified, in response to specific user requests and in response to the Core's vision of what will be needed in the future. AFNI is "pushed" to NIH computers whenever updates are made; users at non-NIH sites must download and install the software themselves. The Core also assists NIH labs in setting up computer systems for use with AFNI, and maintains an active Web site. Notable developments during FY 2014 include: - The AFNI method for nonlinear warping of 3D brain images was improved and extended, and its usage is beginning to pick up. In particular, this method has been used to create a pediatric brain atlas at different ages, and is also being used for aligning pre- and post-surgical resection images in tumor patients. - Exciting new software for interactive analysis and display of brain connectivity maps was developed; the user can see functional and anatomical connectivity maps together, selecting what is visible by various criteria, overlaying other information (such as intra-surgical mapping data), and do it all smoothly and in 3D. This SUMA software has created excitement among neurosurgeons involved in deep brain stimulation (DBS) efforts, and is being used in collaboration with Helen Mayberg's group (infra). This effort also involves the implementation of techniques for aligning multiple types of images from single subjects (MRI, PET, CT) to facilitate precise electrode placement. - Other brain atlas work that continues includes the ability to interactively query from within AFNI (e.g., while pointing at a brain location) remote Web resources, such as human gene expression maps from the Allen Institute. The macaque template and connectivity atlas being developed by K Saleem are being incorporated into AFNI. Of the major (F)MRI packages, AFNI is unique in its visualization abilities and the ability to make interactive queries of functional, anatomical, and connectivity atlases. - Software was created for Chris Baker's group to do population receptive field mapping in visual cortex. Extramural Collaborations: - We worked with Dr Paul Taylor (African Institute for Mathematical Sciences) to develop several new tools for AFNI, including diffusion-tensor (white matter) tract tracing. - We continued working with Dr Helen Mayberg (Emory University) to enhance AFNI to aid her research into pre-surgical planning for deep brain stimulation. - Collaboration with Dr Nitin Tandon of UT Houston resulted in 2 publications in the field of intra-surgical mapping in epilepsy patients. Public Health Impact: Thus far in FY 2014 (Oct-Aug), the principal AFNI publication has been cited in 417 papers (cf Scopus). Most of our work supports basic research into brain function, but some of our work is more closely tied to or applicable to specific diseases: - We collaborate with Dr Alex Martin (NIMH) to apply our resting state analysis methods to autism spectrum disorder. - We consult very frequently with NIMH researchers (e.g., Drs Pine, Ernst, Grillon, Leibenluft) working in mood and anxiety disorders. - We consult with Dr Elliot Stein (NIDA) in his research applying FMRI methods to drug abuse and addiction, and to Drs Hommer/Momenan (NIAAA) in their studies of alcholism. - Our Gd-DTPA nonlinear analysis method is used in the NIH Clinical Center to analyze data from brain cancer patients. - Our precise registration tools (for aligning functional MRI scans to anatomical reference scans) are important for individual subject applications of brain mapping, such as pre-surgical FMRI planning. - Our realtime FMRI software is being used for studies on brain mapping feedback in neurological disorders, and is also used daily for quality control at the NIH FMRI scanners. and also at a few extramural sites. - Our statistical methods are being applied to epilepsy patients undergoing surgical planning with electro-corticography. Publications: #1-5 originated in the Core. #6-19 are from other NIH groups, who included Core authors as significant contributors. #20-21 are from UT Houston, who included a Core author as a significant contributor. The remaining papers listed are NIMH-authored publications that cited the primary AFNI paper, as an indication of their use of the Core facility. Papers from NIH-but-not-NIMH authors are not included here, nor are papers from extramural researchers