Opportunities for Statistical Modeling and Computation at the National Institute of Mental Health (NIMH), NIH

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Presenter: Abera Wouhib, Ph.D. Mathematical Statistician with Opportunities for Statistical Modeling and Computation at the National Institute of Mental Health (NIMH), NIH Greg Farber, Ph.D. Director, Office of Technology Development and Coordination Michele Ferrante, Ph.D. Program Director, Theoretical and Computational Neuroscience and Computational Psychiatry Joint Statistical Meeting, Baltimore MD July 30, 2017

NIMH Research Priorities Four Strategic Objectives 1. Define the mechanisms of complex behaviors 2. Chart mental illness trajectories to determine when, where, and how to intervene 3. Strive for prevention and cures 4. Strengthen the public health impact of NIMH-supported research

The BRAIN Initiative Provides the roadmap for the NIH initiative A focus on tool development (devices and analysis techniques) to understand circuits and networks statistic appears 57 times in this document.

The BRAIN Initiative 4 http://www.braininitiative.nih.gov

The BRAIN Initiative RFA-EB-15-006 BRAIN Initiative: Theories, Models and Methods for Analysis of Complex Data from the Brain (R01) Understand brain function from complex neuroscience data Theories to organize/unify data and infer general principles Mathematical/statistical models to drive testable hypothesis Methods for complex data analysis and feature detection Tools that can be used by the larger neuroscience community 5 http://braininitiative.nih.gov/funding_active.htm

6 The BRAIN Initiative

Collaborative Research in Computational Neuroscience (CRCNS) National Institute of Neurological Disorders and Stroke National Center for Complementary and Integrative Health National Institute on Alcohol Abuse and Alcoholism Eunice Kennedy Shriver National Institute Of Child Health and Human Development National Institute on Drug Abuse National Institute of Mental Health National Institute on Deafness and other Communication Disorders National Eye Institute National Institute of Biomedical Imaging and Bioengineering 7

Theoretical and Computational Neuroscience Program Division of Neuroscience and Basic Behavioral Science, NIMH This Program supports empirical and theoretical studies of self-organizing behavior in neuronal systems, mathematical approaches to modeling non-stationary neuronal processes, functional imaging of dynamical systems, and the modeling of all levels of neuronal processing, from single cell activity to complex behaviors. Projects typically combine mathematical and computational tools with neurophysiological, neuroanatomical, or neurochemical techniques in order to decipher the mechanisms underlying specific neuronal and behavioral systems. Computational Psychiatry Program Division of Translational Research, NIMH ~NEW This program fosters biologically-based computational frameworks to identify and validate biomarkers and novel treatment targets relevant to the prevention, treatment, and recovery of psychiatric disorders. The program supports translational research using analytical approaches for the prediction of risk and treatment response and the understanding of the pathophysiology underlying mental disorders. Contact: michele.ferrante@nih.gov 8

Informatics Data Archive NIMH has made significant investments in the area of informatics. The largest investment is in the NIMH Data Archive (NDA). This is a single Oracle database that holds all clinical research funded by NIMH and welcomes research from others. The Stanley Foundation and others are taking advantage of our willingness to hold data related to mental health by also requiring their awardees to deposit data. There are currently 4 websites that allow the community to access the NDA Nat l Database for Autism Research https://ndar.nih.gov/ Nat l Database for Clinical Trials http://ndct.nimh.nih.gov/ RDoC Database http://rdocdb.nimh.nih.gov/ Pediatric MRI http://pediatricmri.nih.gov/nihpd/info/index.html

National Database for Autism Research Overview Joint initiative supported by NIMH, NICHD, NINDS, and NIEHS Federal data repository Contains data from human subjects related to autism (and control subjects). Subjects have consented to broad data sharing. Data are available to the research community through a not too difficult application process Summary data are available to everyone with a browser (http://ndar.nih.gov) Begun in late 2006, and first data was received in 2008 The data types include demographic data, clinical assessments, imaging data, and omic data Currently has data available from over 85,000 subjects ~500TB of imaging and omic data is securely stored in the cloud NDAR is the oldest of the NDA websites and has the functionality that will ultimately be available via all of them.

Data Dictionary The First Building Block The NDAR data dictionary is one of the key building blocks for this repository. It provides a flexible and extensible framework for data definition by the research community. 1200+ instruments, freely available to anyone 120,000+ unique data elements and growing A research community platform for defining the complex language characterizing autism research Clinical Genomics/Proteomics Imaging Modalities Curated by NDAR Allows investigators to quickly perform quality control tests of their data without submitting data anywhere. We expect 2000+ data instruments in the next few years, so we are searching for partners to help devise strategies to aid with queries across the data elements.

NIH Supported Data Repositories The NIMH Data Archives are not the only game in town. This listing contains 65 repositories, and there are undoubtedly others. NIH sometime announces R03s for data re-analysis.

Directory of Federal Neuroscience Research Funding https://www.nimh.nih.gov/funding/neuroscience-research-funding-contacts-in-the-federal-government-2017.shtml 13

14 NIMH Funding Initiatives

Rigor, Reproducibility and Statistical Power in Mental Health Research: Request for Information Notice Number: NOT-MH-17-036 Released Date: July 14, 2017 Purpose: Seeking input on statistical issues with the goal of improving the rigor and reproducibility of mental health research Possible comments: Innovative study designs Optimizing sample size while maintaining feasibility What are the barriers to submitting adequately powered studies Developing guidance to applicants to improve rigor in applications Developing guidance to the peer-review process regarding statistical rigor Facilitating clinical results that can be reproducible and advance mental health Contact: Abera Wouhib, Math. Statistician (NIMH/NIH) email: abera.wouhib@nih.gov 16

How to Navigate the NIH Grants System Plan & prepare your application Submission Payment or Revision Scientific Merit Review Council Review Summary Statement Program Review 17