The main mission of the Core is to help NIH researchers with analyses of their fMRI (brain activation mapping) data. Along the way, we also help non-NIH investigators, mostly in the U.S. 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 involved 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 recognize bad data? - 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 once at the NIH during FY 2015 to over 140 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 2 non-NIH sites (the expenses for these trips were covered by the hosts): Tuebingen (Germany) and Cape Town (South Africa). 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. 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 2015 include: - The software for interactive analysis and display of brain connectivity was further extended, allowing more types of data to be displayed -- including CIFTI formatted datasets from the Human Connectome Project. - The single-subject fMRI data analysis script and GUI have been extended to give the user more control over the data processing options. - A new software tool, 3dMVM (Multi-Variate Modeling), was created to allow for complex inter-subject analyses, allowing for unbalanced ANOVA-like designs with subject- and factor-level covariates, and for multiple measurements per subject/per factor. This powerful tool lets the user set up the analysis symbolically, without having to code the design matrix by hand -- the program takes care of that. - The FATCAT package for diffusion MRI analysis was extended to be faster and more accurate, and to be more closely integrated with the AFNI data visualization package. The author of FATCAT has accepted an offer to join the Core, and is currently in the on-boarding process. Public Health Impact: Thus far in FY 2015 (Oct-Aug), the principal AFNI publication has been cited in 304 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 alcoholism. - 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 fMRI scans to anatomical reference scans) are important for individual subject applications of brain mapping, such as pre-surgical fMRI planning. - Our real-time fMRI software is being used for studies on brain mapping feedback in neurological disorders, is used daily for quality control at the NIH fMRI scanners, and is also used at a few extramural sites. - Our statistical methods are being applied to epilepsy patients undergoing surgical planning with electro-corticography. Publications: #1-12 are papers that include Core authors. The remaining publications are from NIMH authors, who 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 (due to limitations in the bibliography system). Personnel: The core of the Core is its people. The mission of the Core is to help researchers, and all of the Core staff are helpful and professional. Each Core member consults with users regularly, and all Core members are held in high esteem by NIMH fMRI-based investigators. Late in 2015, Dr. Ziad Saad left the Core for an opportunity in industry. His loss is sorely felt. A new staff scientist candidate has been recruited to replace him, and we are looking forward to his arrival.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Scientific Cores Intramural Research (ZIC)
Project #
1ZICMH002888-09
Application #
9152154
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
9
Fiscal Year
2015
Total Cost
Indirect Cost
Name
U.S. National Institute of Mental Health
Department
Type
DUNS #
City
State
Country
Zip Code
Moraczewski, Dustin; Chen, Gang; Redcay, Elizabeth (2018) Inter-subject synchrony as an index of functional specialization in early childhood. Sci Rep 8:2252
Seidlitz, Jakob; Sponheim, Caleb; Glen, Daniel et al. (2018) A population MRI brain template and analysis tools for the macaque. Neuroimage 170:121-131
Warton, Fleur L; Taylor, Paul A; Warton, Christopher M R et al. (2018) Prenatal methamphetamine exposure is associated with corticostriatal white matter changes in neonates. Metab Brain Dis 33:507-522
Riva-Posse, P; Choi, K S; Holtzheimer, P E et al. (2018) A connectomic approach for subcallosal cingulate deep brain stimulation surgery: prospective targeting in treatment-resistant depression. Mol Psychiatry 23:843-849
Finn, Emily S; Corlett, Philip R; Chen, Gang et al. (2018) Trait paranoia shapes inter-subject synchrony in brain activity during an ambiguous social narrative. Nat Commun 9:2043
Haller, Simone P; Kircanski, Katharina; Stoddard, Joel et al. (2018) Reliability of neural activation and connectivity during implicit face emotion processing in youth. Dev Cogn Neurosci 31:67-73
Silson, Edward H; Reynolds, Richard C; Kravitz, Dwight J et al. (2018) Differential Sampling of Visual Space in Ventral and Dorsal Early Visual Cortex. J Neurosci 38:2294-2303
Branco, Mariana P; Gaglianese, Anna; Glen, Daniel R et al. (2018) ALICE: A tool for automatic localization of intra-cranial electrodes for clinical and high-density grids. J Neurosci Methods 301:43-51
Torrisi, Salvatore; Chen, Gang; Glen, Daniel et al. (2018) Statistical power comparisons at 3T and 7T with a GO / NOGO task. Neuroimage 175:100-110
Choi, Ki Sueng; Noecker, Angela M; Riva-Posse, Patricio et al. (2018) Impact of brain shift on subcallosal cingulate deep brain stimulation. Brain Stimul 11:445-453

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