The Challenge
Recent years have ushered in the era of discovery science for human brain function and structure. Inspired by the growing success of connectomics, and first looks at large-scale datasets amassed through collaborative and open-science initiatives, the race to map the human connectome and its associations with phenotypic variation is underway. In particular, the medical community aspires to normative assessments of human brain function and structure across the lifespan. Such assessments will enable the identification of perturbations in developmental, maturational and aging processes associated with the presence or risk of eventual development of neuropsychiatric illness. Unfortunately, despite major advances in imaging techniques, analytic methodologies, and neuroscientific understanding, we lack the datasets necessary to make the community’s ambitions a reality.

One Step Closer to a Solution: The Nathan Kline Institute-Rockland Sample
While no single effort can create the large-scale datasets necessary to deliver the entirety of normative assessments of the lifespan, the Nathan S. Kline Institute for Psychiatric Research is actively working to provide a model through which these data can be acquired and shared. The Nathan Kline Institute-Rockland Sample is a large-scale, cross-sectional sample of brain development, maturation and aging (ages 6 – 85 yrs), that is currently in collection and funded by the National Insitute of Mental Health to characterize 1000 community-ascertained participants using state-of-the-art multiplex 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 the International Neuroimaging Data-sharing Initiative (INDI) based at the Neuroimaging Tools and Resources Clearinghouse (NITRC) and genetic samples will be processed and made available through the NIMH Genetics Repository.

What is Innovative About the NKI-Rockland Sample?A Lifespan Design

Nearly 75 percent of mental illness in adults originates prior to age 24 years, and numerous links have been identified between the presence of childhood psychiatric problems and the later onset of adult illness. As such, the developmental origins of most psychiatric illnesses are increasingly being appreciated. Whether considering disorders affecting children, adolescents, adults or the elderly, early detection of disease risk and/or onset is the critical first step in prevention and treatment, respectively. In this regard, the imaging community is increasingly hopeful that normative assessments of brain development, maturation and aging can be obtained. We anticipate that these normative trajectories will facilitate the identification of markers of pathologic development capable of one day informing multiple aspects of clinical assessment and decision-making—ranging from determinations of risk, diagnosis, and prognosis, to the selection and timing of interventions, as well as treatment response monitoring.

Unfortunately, the imaging community remains without a large-scale dataset sampling lifespan—despite it being a crucial first step towards attaining normative assessments of human brain function and structure. The NKI-RS study is taking a key step forward in addressing this gap, through the employment of a cross-sectional lifespan design-sampling individuals between the ages of 6 and 85 years old in the same sample. As will be discussed in the following sections, a unique aspect of the NKI-RS study design that has made this possible is the careful attention given to imaging and phenotypic measures that can be used with individuals of any age. 

Community Design

Brain 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 Study of 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. Recruitment efforts will ensure maximal visibility throughout Rockland County by the distribution of flyers to approximately 100,000 households, as well as the use of social networking and free media.

Imaging the Brain at Unprecedented Speeds

Typically functional MRI allows researchers to measure patterns of brain activity throughout the full brain at a rate of one image every 3 seconds; diffusion imaging, which is commonly used to measure structural connectivity in the brain, can take upwards of 30-60 minutes to obtain high quality images. The Center for Magnetic Resonance Research (CMRR), University of Minnesota, recently developed a novel approach to acquiring functional MRI that has reduced sampling rates down to one image every 400-600 milliseconds for functional MRI studies of brain activity. When applied to diffusion imaging, this technology is now allowing researchers to capture structural connectivity throughout the brain, with great detail, in as little as 7 minutes. Initially developed for the Washington University-University of Minnesota (WU-Minn) consortium of the Human Connectome Project, these sequences have been provided to the NKI-RS effort to ensure the best quality data is obtained in the shortest time possible, given that pediatric and geriatric populations are participating in the study.

Deep Phenotyping

The NKI-RS captures a broad range of behavioral and cognitive phenomenology relevant to psychiatric health and illness, with great detail (i.e., deeply). 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 adn the 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 of the initial plan for the NKI-RS phenotypic protocol and study design, the Child Mind Institute’s Scientific Research Council recommended that the protocol’s administration schedule be decompressed from one to two days (scheduled within 2 weeks of each other) to minimize participant fatigue and burden—thereby protecting the integrity of data collection. In response to these recommendations, the Child Mind Institute has provided the NKI-RS with the funding necessary to decompress the design from a one- to two-day protocol. Additional funding and manpower was also provided to minimize the burden on the NKI-RS staff as well. Minimization of both participant and experimenter burden is essential to the success of scientific endeavors.

State of the Art 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 Child Mind Institute has provided the NKI-RS with a state of the art data capture and management system developed by the Mind Research Network. Named the COllaborative Informatics and Neuroimaging Suite (COINS), this system enables web-based management and administration of all phenotypic assessments (e.g., participant questionnaires), 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.


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