Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5–21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n=664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).

Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5-21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics, and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n = 664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).. CC-BY-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/149369 doi: bioRxiv preprint first posted online Jun. 13, 2017; PURPOSE OF DATA COLLECTIONPsychiatric and learning disorders are among the most common and debilitating illnesses across the lifespan. Epidemiologic studies indicate that 75% of all diagnosable psychiatric disorders begin prior to age 241 . This underscores the need for increased focus on studies of the developing brain 2 . Beyond improving our understanding of the pathophysiology that underlies the emergence of psychiatric illness throughout development, such research has the potential to identify clinically useful markers of illness that can improve the early detection of pathology and guide interventions. Although the use of neuroimaging, neuropsychology, neurophysiology and genetics has made significant strides in revealing biological correlates for a broad array of illnesses, findings have been lacking in specificity 3 . Consequently, progress in finding clinically useful brain-based biomarkers has been disappointing 4,5 .Given the slow pace in biomarker identification, investigators have been prompted to rethink research paradigms and practices. Most notably, the emphasis on mapping diagnostic labels from a clinically defined nosology (e.g., the Diagnostic and Statistical Manual of Mental Disorders (DSM) or the International Classification of Diseases) to varying biological indices has proven to be problematic, as it assumes consistent biological relationships with broad constellations of signs and symptoms 6,7 . Epidemiologists, psychopathologists, geneticists and neuroscientists are reconsidering the relevance of diagnostic boundaries due to the lack of specif...

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To assess whether cocaine exposure in utero affected adrenocortical responsiveness in the neonatal period, salivary cortisol levels were compared between noncocaine-exposed (n = 35) and cocaine-exposed (n = 11) healthy preterm infants just prior to hospital discharge. Cortisol levels were measured under three conditions: Basal--120 min after no disrupting event or behavioral distress; Noninvasive Stressor--30 min after a neurobehavioral examination; Invasive Stressor--30 min after a heel-stick procedure. There were no differences in Basal cortisol levels between the noncocaine-exposed and cocaine-exposed infants, but the cocaine-exposed infants had significantly lower levels in both the Noninvasive and Invasive Stressor conditions. The suppressed cortisol responding to stressful events in cocaine-exposed infants suggests that these infants may have decreased modulation capability to normally stressful events, which could underlie some of the subtle state regulation problems reported.

OBJECTIVES Recent evidence suggests higher prevalence of autism spectrum disorder (ASD) in NICU graduates. This aim of this study was to identify retrospectively early behaviors found more frequently in NICU infants who went on to develop ASD. METHODS Twenty-eight NICU graduates who later received a diagnosis of ASD were compared with 2169 other NICU graduates recruited from 1994 to 2005. They differed in gender, gestational age, and birth cohort. These characteristics were used to draw a matched control sample (n = 112) to determine which, if any, early behaviors discriminated subsequent ASD diagnosis. Behavioral testing at targeted ages (adjusted for gestation) included the Rapid Neonatal Neurobehavioral Assessment (hospital discharge, 1 month), Arousal-Modulated Attention (hospital discharge, 1 and 4 months), and Bayley Scales of Infant Development (multiple times, 4–25 months). RESULTS At 1 month, children with ASD but not control children had persistent neurobehavioral abnormalities and higher incidences of asymmetric visual tracking and arm tone deficits. At 4 months, children with ASD had continued visual preference for higher amounts of stimulation than did control children, behaving more like newborns. Unlike control children, children with ASD had declining mental and motor performance by 7 to 10 months, resembling infants with severe central nervous system involvement. CONCLUSIONS Differences in specific behavior domains between NICU graduates who later receive a diagnosis of ASD and matched NICU control children may be identified in early infancy. Studies with this cohort may provide insights to help understand and detect early disabilities, including ASD.