The Enhanced Nathan Kline Institute-Rockland Sample (NKI-RS)

Multiband Imaging Test-Retest Pilot Dataset

What is the enhanced NKI-RS?
Building on the model of our initial NKI-RS effort, the enhanced NKI-RS will be a large cross-sectional sample of brain development, maturation and aging (ages 6 - 85 yrs), that is currently funded by the NIMH (PI Milham) to characterize 1000 community-ascertained participants using state-of-the-art multiband imaging-based resting state fMRI (R-fMRI) and  diffusion tensor imaging (DTI), genetics, and a deep phenotyping protocol. Designed as an open-access community resource, the NKI-RS will provide researchers with data for the testing of existing hypotheses, as well as the generation of novel hypotheses through the application of data exploration techniques. Imaging datasets will be shared on a weekly basis through Neuroimaging Tools and Resources Clearinghouse (NITRC) and genetic samples will be processed and made available through the NIMH Genetics Repository.

How does the enhanced NKI-RS differ from the original NKI-RS? 

Imaging. Recently developed multiband echo planar Imaging (Moeller et al., 2010) and multiplexed echo planar imaging (Feinberg et al., 2010) approaches enable the acquisition of functional MRI and diffusion imaging data with unprecedented sampling rates for full-brain coverage through the acquisition of multiple slices simultaneously in the same time it takes to obtain a single slice image using standard EPI (Feinberg et al. [in press], see Smith et al. [2012] for initial application of Multiband EPI with recent improvements (Xu et al. 2012; Proc. Int. Soc. Mag Reson Med). The Center for Magnetic Resonance Research (CMRR), University of Minnesota, where these sequences are developed for the Washington University-University of Minnesota (WU-Minn) consortium of the Human Connectome Project, has provided the NKI-RS effort with the latest version of the Multiband EPI sequence (Xu et al. 2012) and associated image reconstruction algorithms, enabling the acquisition of state-of-the-art imaging datasets for this large-scale imaging effort.  Specific parameter selections were based on initial pilot data to optimize image quality on our scanner.  As specified in detail below, two R-fMRI sequences are included in the protocol - a TR = 645msec (3mm isotropic voxels, 10 minutes) to provide optimal temporal resolution and TR = 1400msec (2mm isotropic voxels, 10 minutes) to provide optimal spatial resolution. A standard EPI sequence (TR = 2500msec, 3mm isotropic voxels, 5 minutes) is included for reference. Given the pediatric and geriatric populations included in the sample, the enhanced NKI-RS includes a 137-direction DTI sequence allowing us to obtain maximal data in minimal time. We are very grateful to WU-Minn HCP members at CMRR for guidance and assistance in the design, implementation and troubleshooting of these sequences and their reconstruction. These sequences and the associated image reconstruction algorithms for the Siemens platforms are available for distribution from CMRR (

Phenotyping. The enhanced NKI-RS expands upon the phenotypic protocol of the original NKI-RS and captures a broad range of behavioral and cognitive phenomenology relevant to psychiatric health and illness. The validity and value of assessments were evaluated by consulting leaders in the field of psychiatric phenotyping. To maximize scientific overlap, assessment selection was guided through consultation with and review of other phenotypic data collection and sharing initiatives, such as Brain Genomics Superstruct, the Human Connectome Project, Brain Behavior Laboratory at the University of Pennsylvania. Preference was given to measures that are available in forms suitable for individuals across the targeted age-range and with age-normed data; though exceptions were made when deemed justified by consensus. The protocol strives to attain both breadth and depth in terms of psychiatrically relevant phenotypic variables. Following review and recommendations by the Child Mind Institute's Scientific Research Council, the enhanced protocol's administration schedule was decompressed from one to two days (scheduled within 2 weeks of each other) to accommodate the expanded phenotypic protocol and minimize subject fatigue and burden - thereby protecting the integrity of data collection. To the right is the complete assessment protocol for the enhanced NKI-RS.

Neuroinformatics Infrastructure. Given the substantial increase in phentoyping, as well as the time-consuming and error-prone nature of collecting and managing data from paper and pencil assessments, the enhanced NKI-RS adopted the COllaborative Informatics and Neuroimaging Suite (COINS) as its core internal infrastructure. This system enables web-based management and administration of all phenotypic assessments, as well as the automatic integration of phenotypic and
neuroimaging data in an easily searchable platform. Pilot testing of the COINS with participants from the NKI-RS pilot effort indicated increased participant satisfaction and decreased data management error.

Community Design. Imaging studies tend to be opportunistic in their recruitment without regard for geographic, socioeconomic, ethnic, and racial representation of the community from which the sample is derived.  Although understandable, such strategies increase the risk of artifactual recruitment biases.  In response to this concern, the enhanced NKI-Rockland Sample will follow the model of epidemiologic studies and imaging efforts such as the NIH Normal Brain Development, by carefully controlling recruitment and enrollment in order to maximize the community representativeness of the sample and minimize biases inherent to opportunistic recruiting. Specifically, we will ensure that the population of each zip-code in Rockland County is proportionately represented in the sample. As demonstrated by the 2009 U.S. census, Rockland County is strikingly representative of the U.S. population in key demographic measures as seen in the table to the right. Recruitment efforts will ensure maximal visibility throughout Rockland County by th
e distribution of flyers to approximately 100,000 households, as well as social networking and free media.
The Multiband Test-Retest
Pilot Dataset
Prior to launch of the Enhanced NKI-RS, an initial test-retest dataset was obtained to assess the reliability of multiband R-fMRI and DTI scans. The dataset is primarily composed of individuals from the initial NKI-RS - for these individuals psychiatric assessment information is available and included (participants were not excluded due to history of illness - see phenotypic information file for diagnostic information).
In addition to R-fMRI and DTI, we included: 1) simple visual checkerboard stimulation fMRI scans to allow for assessment of traditional fMRI data quality metrics (e.g., contrast-to-noise ratio), 2) breath holding data to enable assessment of regional differences in vascular responsiveness, and 3) eye movement calibration scans to enable the assessment of eye-movement related artifacts which may be particularly troublesome for multiband sequences since several slices are acquired simultaneously.

Important Analytic Considerations for Multiband Imaging
Innovations associated with multiband imaging (e.g., simultaneous acquisition of multiple slices) can introduce novel challenges for functional MRI imaging preprocessing and analyses.  When using this data please keep in mind the following caveats provided by Christian Beckmann and Steve Smith from the HCP:
  • The increased number of time points obtained when using short TR will change the temporal degrees of freedom. This can be used to drive investigations into the temporal characteristics of resting-state patterns (see Smith et al, 2012). However, the effective temporal autocorrelation will change. This needs to be corrected for, e.g. when converting regression coefficients or correlation coefficients to T, Z or P statistics  (for more discussion see Feinberg et al., 2010)  
  • The spatial smoothness of the data may be affected. In particular, smoothness can be non-stationary, so Gaussian-Random Field Theory-based inference (e.g. cluster-correction in in SPM or FSL) might not be suitable.
  • Because multiple slices are excited simultaneously, simple slice time correction will not work and each slice will need to be corrected using custom timing information. Given the short effective TR it is probably less important, though.
Repeated Scans

Single Acquisition Scans

Stimulus Design Files

Stimulus Execution Scripts (for use with Vision Egg)

We are providing the entirety of the sample obtained.  It is up to the individual user to make quality determinations for their respective analysis purposes. 

Usage Agreement
Creative Commons License: Attribution - Non-Commercial

The Enhanced NKI-RS Team

Michael Milham (PrincipaI Investigator; Deputy Director of Human Imaging, NKI), Bennett Leventhal (Deputy Director, NKI), F. Xavier Castellanos (Director of Child and Adolescent Psychiatry, NKI), Kate Nooner (Clinical Director, NKI Outpatient Research), Russ Tobe (Medical Director, NKI
Outpatient Research), Stan Colcombe (Director of Human Imaging, NKI)

Clinical Evaluation and Phenotyping
Melissa Benedict, Alexis Moreno, Laura Panek, Steve Zavitz, Ayesha Anwar, Shaquanna Brown, Caitlin Hinz, Stephanie Kamiel, Michelle Kaplan, Anna Rachlin.

Cathy Hu, Raj Sangoi, Steve Zavitz, Cameron Craddock

Programming, Technical and Analytic Support

Sharad Sikka, Qingyang Li, Brian Cheung, Ranjit Khanuja, David Lewis, Chao-Gan Yan

Neuroinformatics (Mind Research Network)
Vince Calhoun, Will Courtney, Margaret King, Susan Lane, Adam Scott, Runtang Wang, and Dylan Wood

Dawn Thomsen, Marissa Jones Issa, Nancy Duan

Miscellaneous Support Guidance
Bharat Biswal, Chrissie Cox,
Adriana Di Martino, David Guilfoyle, Matt Hoptman, Brett Lullo, Clare Kelly, Daniel Margulies, Nunzio Pomara, John Sidtis, Xinian Zuo

*special thanks to Cameron Craddock for his assistance in designing the test-retest dataset and helping to troubleshoot its various phases, as well as providing the task paradigms; to Kamil Urgurbil, Eddie Auerbach, Junquian Gordon Xu and Steen Moeller from the HCP for assistance with the implementation of the multiband sequences and reconstruction algorithms; to Satrajit Ghosh for his guidance in the development of our DICOM anonymization protocol; and as always - to Maarten Mennes for his efforts overseeing the INDI team.

Principal support for the enhanced NKI-RS project is provided by the NIMH BRAINS R01MH094639-01 (PI Milham). Funding for key personnel also provided in part by the New York State Office of Mental Health and Research Foundation for Mental Hygiene. Funding for the decompression and augmentation of administrative and phenotypic protocols provided by a grant from the Child Mind Institute (1FDN2012-1).  Additional personnel support provided by the Center for the Developing Brain at the Child Mind Institute, as well as NIMH R01MH081218, R01MH083246 and R21MH084126. Project support also provided by the NKI Center for Advanced Brain Imaging (CABI), the Brain Research Foundation (Chicago, IL), and the Stavros Niarchos Foundation.




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