David C. Van Essen - US grants

During normal postnatal development, mammalian skeletal muscles undergo an orderly process of synapse elimination, whereby each muscle fiber loses all but one of the multiple synapses with which it starts at birth. Dr. Van Essen will study several aspects of synaptic specificity and plasticity in the soleus muscle of the rabbit, using a variety of anatomical and physiological techniques. One objective is to ascertain the way in which two distinct populations of motor neurons (fast or slow) innervate their respective populations of muscle fibers. He will determine the incidence of mismatched connections (fast motor axons onto slow muscle fibers and vice versa) during the stage of extensive polyinnervation, and he will test for differences in the number of synapses initially made onto fast and slow fibers. Another objective is to study the regional distribution of muscle fibers within individual motor units and to ascertain whether this distribution within the muscle changes during the period of synapse elimination. Finally, Dr. Van Essen will determine whether there are changes in neuromuscular connections during a period of late postnatal development, when many muscle fibers are known to convert from fast to slow contractile type. These studies may provide valuable insights concerning the cellular basis of synaptic plasticity and the rules governing orderly rearrangements of synaptic connections.

DESCRIPTION(provided by the applicant): Visual cortex in primates includes dozens of distinct areas arranged in a mosaic that occupies much of the cerebral cortex. This proposal will use physiological and anatomical methods to study form processing in the macaque monkey. In addition, anatomical and computerized brain mapping methods will be used to analyze and compare the arrangement of visual areas in humans and macaques. Experiments on form vision will involve recordings from neurons in visual areas V2 and V4 of the macaque. One project will analyze the spatial organization of classical receptive fields and nonclassical receptive field surrounds in area V2. The objective is to reveal neurophysiological mechanisms underlying the selectivity for textures and complex shapes that are encountered in many V2 neurons. A second project will determine whether surface features and object boundaries are analyzed by different neuronal populations in area V2 and whether neurons in V2 are directly implicated in specific aspects of form perception. A third project will study the representation of three-dimensional shapes in area V4. Neural responses to simulated bumps, indentations, and flat surfaces will be analyzed to determine whether cells in V4 explicitly represent the sign of surface curvature. The proposed comparisons of visual cortical areas in humans will make use of surface-based atlases and surface-based warping to deform the macaque map to the shape of the human cortical map. These comparisons will provide an objective basis for evaluating possible homologies between visual areas in the two species. Collectively, these experiments should reveal important principles of organization and function in primate visual cortex that are relevant to the understanding and treatment of functional deficits resulting from strokes and other neurological disorders.

We request funding for the acquisition of equipment needed for the 3-dimensional (3-D) reconstruction and analysis of biological structures. The major equipment items are a laser-scanning confocal microscope (Zeiss LSM) and a high-performance 3-D graphics workstation (Silicon Graphics IRIS VGX series). These will be part of an integrated effort in biological imaging, which will involve 14 research labs in the Biology Division at Caltech. One set of projects will utilize the confocal system for studying single cells, early embryos, and other structures at the microscopic level. Another set of projects will be aimed at generating 3-D reconstructions of macroscopic structures, including the brains of monkeys, humans, and other species. For many of these projects, we will be able to use commercially available software for image analysis and 3-D reconstruction. We also intend to develop software for specialized applications, but this activity will not be directly supported by the requested funding. To promote and coordinate these efforts, we have established a Biological Imaging Center on campus. This will be a professionally staffed facility, and we anticipate that it will substantially enhance the efficiency, ease, and flexibility with which the requested equipment will be used.

DESCRIPTION (provided by applicant): Neuroscientists are faced with a torrent of experimental data about the structure, function, and development of the brain in health and disease. To aid in coping with this flood, the present project aims to provide the neuroscience community with (i) a well-integrated set of software tools for visualizing, analyzing, accessing, and communicating information about the cerebral and cerebellar cortex and (ii) a set of surface-based atlases that provide a compendium of information about human, monkey and rodent cortex. One objective is to implement a unified software application (Caret) that will carry out fully automated segmentation (to capture the shape of the cortex in individual brains), plus multiple stages of surface-based analysis. These analyses will include generating cortical flat maps and spherical maps, identifying cortical sulci, mapping cortical thickness, and registering individuals to the atlas map. A second objective is to enhance the Surface Management System (SuMS) database, by incorporating powerful search capabilities, and by improved methods for visualizing search results, both online and offline. SuMS will be a distributed database network that allows local file storage with multiple security levels as well as access to the central SuMS repository. A third objective is to improve the methods for surface-based registration of one cerebral hemisphere to another, in order to better compensate for individual variability within a species and to provide improved methods for making comparisons across species. A fourth objective is to expand the mapping of experimental data from a variety of sources onto surface-based atlases of human, macaque, rat, and mouse cerebral and cerebellar cortex. A major focus will be on the development of probabilistic maps of visual areas in monkey and human cortex. Attainment of these overall objectives will allow neuroscientists everywhere to access many types of experimental information about cerebral and cerebellar cortex with much greater ease and flexibility than is currently possible.

ABSTRACT NOT PROVIDED

DESCRIPTION (provided by applicant): Preterm birth is a major public-health issue because of its increasing incidence combined with the frequent occurrence of subsequent behavioral, neurological, and psychiatric challenges faced by surviving infants. Approximately 10-15% of very preterm children (born <30 weeks gestational age) develop cerebral palsy, and 30 - 60% of very preterm children experience cognitive impairments. These impairments include visual-motor problems, attentional difficulties, impaired memory, delayed acquisition of language, executive dysfunction, learning disabilities, poor social skills, and higher rates of social withdrawal, anxiety and depression. In addition, an increased prevalence of developmental disorders such as attention deficit/hyperactivity disorder, autism and schizophrenia, has been described in the preterm population. These adverse outcomes are related to white matter (WM) and grey matter (GM) injury sustained during the neonatal period and its effects on subsequent brain development. We seek to develop imaging biomarkers, measurable during infancy, that provide sensitivity and specificity in identifying infants at risk for poor neurodevelopmental outcome. The biomarkers will consist of the following magnetic resonance (MR) imaging measures: 1) conventional T1- and T2-weighted images, 2) volumetry (volumes for cortical GM, deep nuclear GM, myelinated WM, unmyelinated WM, and cerebrospinal fluid), 3) diffusion tensor imaging (apparent diffusion coefficient, relative anisotropy, axial and radial diffusivity), and 4) surface-based morphometry (integrated folding index, average sulcal depth, cortical surface area, percentage of buried cortex). The main cohort of this study will consist of 120 very preterm infants born <30 weeks gestational age. They will undergo MR studies soon after birth, at 30 weeks postmenstrual age (PMA), 34 weeks PMA, and term equivalent. Infants enrolled during Year 1 (n = 30) will also be imaged at age 4 years. The MR indices listed above will be compared with MR data from healthy control subjects and clinical outcome data obtained at term equivalent and 2 and 4 years of age. The proposed studies are designed to engender a deeper understanding of the nature and timing of cerebral injury, laying the groundwork for the development of neuroprotective strategies and improving clinical practices. The longitudinal design will allow us to study both structural abnormalities and compensatory changes in response to injury. Identification during the newborn period of infants at high risk for poor developmental outcome will allow early targeting of therapy services to these infants. If successful, the proposed studies will lead to improved outcomes for prematurely-born infants. Project Narrative: This study is designed to use magnetic resonance imaging to improve our understanding of the brain injury sustained by prematurely-born infants. This understanding has the potential to improve clinical practices and assist with the development of medications to reduce injury in these babies, ultimately reducing disabilities. It will also help identify those infants who are at high risk for developing cerebral palsy or mental retardation so they can be provided early access to therapy services.

DESCRIPTION (provided by applicant): This project will characterize adult human brain circuitry, including its variability and its relation to behavior and genetics. To achieve this ambitious objective, a broad-based multi-institutional consortium of distinguished investigators will acquire cutting-edge neuroimaging data in 1,200 healthy adult humans along with behavioral performance data and blood samples for genotyping. The main cohort of subjects will be twins plus non-twin siblings - a strategy that enables powerful analyses of heritability and genetic underpinnings of specific brain circuits. Comprehensive connectivity maps will be generated for each individual and for population averages using sophisticated data analysis methods. This human connectome will be expressed relative to functional subdivisions (parcels) defined by connectivity and by classical architectonic methods. Data from these maps will reveal fundamental aspects of brain network organization. A powerful, user-friendly informatics platform will be implemented to facilitate the management, analysis, visualization, and sharing of these rich and complex datasets. Because these tools and datasets will have Immediate and long range potential to influence neuroscience research in health and disease, extensive outreach efforts are planned for promoting their widespread awareness and usage. The imaging modalities include three types of magnetic resonance imaging: (i) diffusion imaging using HARDI methods to map structural connectivity; (ii) resting-state fMRI (R-fMRI) to reveal maps of functional connectivity; (iii) task-fMRI (T-fMRI) to reveal brain activation patterns associated with a broad set of behavioral tasks. Magneto-encephalography (MEG) and also EEG will be used to characterize dynamic patterns of neural activity that can be related to structural and functional connectivity maps. Imaging will benefit from a customized 3T scanner developed for this project and ultimately installed at Washington University, a new 7T scanner at the University of Minnesota, and improved pulse sequences and custom coils to be implemented during the project's optimization phase. By scanning all subjects at 3T and subsets at 7T and with MEG, the complementary strengths of each imaging modality will be utilized and the overall impact of the data collection and analysis strategy will be maximized. Consortium members have contributed greatly to the recent progress in data acquisition and analysis strategies that make the Human Connectome Project technically feasible. Major additional advances anticipated during the project's optimization phase will lead to unprecedented fidelity of the structural and functional connectivity maps to be obtained during the production phase.

? DESCRIPTION (provided by applicant): This project will establish a Connectome Coordination Facility (CCF) by capitalizing on recent successes of the Human Connectome Project (HCP), which has acquired, analyzed, and shared multimodal neuroimaging data and behavioral data on a large population of healthy adults. Major advances by the HCP include (i) the establishment of data acquisition protocols that yield high quality data across multiple modalities; (ii) the implementation of preprocessing pipelines that take full advantage of the high quality imaging data; and (iii) the establishment of a robust informatics infrastructure that has allowed widespread sharing of the HCP data within the neuroimaging and neuroscience communities. The CCF will build on these accomplishments and serve the human neuroimaging community in three ways. One aim is to provide consultation and support services to the research community for the primary purpose of harmonizing image acquisition protocols with those of the HCP. The effort will establish a help desk whose support functions will include transfer of data acquisition sequences and image reconstruction algorithms; providing updates and improvements for these sequences and algorithms; harmonization of imaging protocols and image reconstruction support for different software platforms and versions; and consultation for potential problems (e.g. image artifacts). A second aim is to provide services that maximize comparability of data acquired by CCF contributors. These services will include pre-data acquisition guidance to contributors to ensure that each project's behavioral data are obtained using HCP-compatible methods. This will entail coordination with data contributors to develop mechanisms to streamline transfers of de-identified data from the study sites to the CCF database. The data from each study will include the unprocessed images, minimally preprocessed data generated by each project's internal pipelines, and all data associated with the project's behavioral battery. Manual and automated quality control procedures will be implemented based on existing HCP methods to generate quality metrics that will be published with the data. A standardized set of pipelines will be run in order to produce minimally preprocessed data that is fully harmonized with the other data sets in the CCF database. A third aim is to maintain the existing ConnectomeDB data repository infrastructure for Human Connectome Data and expand it to include Connectome data from other research laboratories that are funded as U01 projects under the Connectomes Related to Human Diseases RFA. The platform will be developed and operated following policies and procedures vetted by the HCP to ensure the privacy and security of the data hosted by the CCF. Together, these three aims will establish the CCF as a central hub for connectomics data aggregation and sharing. The CCF's suite of harmonization services from data acquisition through data sharing will ensure an unprecedented level of compatibility across data sets. The resulting database will enable the scientific community to conduct novel analyses to better understand brain function in health and disease.

? DESCRIPTION (provided by applicant): The major technological and analytical advances in human brain imaging achieved as part of the Human Connectome Projects (HCP) enable examination of structural and functional brain connectivity at unprecedented levels of spatial and temporal resolution. This information is proving invaluable for enhancing our understanding of normative variation in young adult brain connectivity. It is now timely to use the tools and analytical approaches developed by the HCP to understand how structural and functional wiring of the brain changes during the aging process. Using state-of-the art HCP imaging approaches will allow investigators to push our currently limited understanding of normative brain aging to new levels. We propose an effort involving a consortium of five sites (Massachusetts General Hospital, University of California at Los Angeles, University of Minnesota, Washington University in St. Louis, and Oxford University), with extensive complementary expertise in human brain imaging and aging and including many investigators associated with the original adult and pilot lifespan HCP efforts. This synergistic integration of advances from the MGH and WU-MINN-OXFORD HCPs with cutting-edge expertise in aging provides an unprecedented opportunity to advance our understanding of the normative changes in human brain connectivity with aging. Aim 1 will be to optimize existing HCP Lifespan Pilot project protocols to respect practical constraints in studying adults over a wide age range, including the very old (80+ years). Aim 2 will be to collect high quality neuroimaging, behavioral, and other datasets on 1200 individuals in the age range of 36 - 100+ years, using matched protocols across sites. This will enable robust cross-sectional analyses of age-related changes in network properties including metrics of connectivity, network integrity, response properties during tasks, and behavior. Aim 3 will be to collect and analyze longitudinal data on a subset of 300 individuals in three understudied and scientifically interesting groups: ages 36-44 (when late maturational and early aging processes may co-occur); ages 45-59 (perimenopausal, when rapid hormonal changes can affect cognition and the brain); and ages 80 - 100+ (the `very old', whose brains may reflect a `healthy survivor' state). The information gained relating to these important periods will enhance our understanding of how important phenomena such as hormonal changes affect the brain and will provide insights into factors that enable cognitively intact function into advanced aging. Aim 4 will capitalize on our success in sharing data in the Human Connectome Project (HCP), and will use these established tools, platforms, and procedures to make this data publicly available through the Connectome Coordination Facility.

? DESCRIPTION (provided by applicant): The major technological and analytical advances in human brain imaging achieved as part of the Human Connectome Projects (HCP) enable examination of structural and functional brain connectivity at unprecedented levels of spatial and temporal resolution. This information is proving crucial to our understanding of normative variation in adult brain connectivity. It is now timely to use the tools and analytical approaches developed by the HCP to understand how structural and functional wiring of the brain develops. Using state-of-the art HCP imaging approaches will allow investigators to push our currently limited understanding of normative brain development to new levels. This knowledge will critically inform prevention and intervention efforts targeting well known public health concerns (e.g., neurological and psychiatric disorders, poverty). The majority of developmental connectivity studies to date have used fairly coarse resolution, have not been multi-modal in nature, and few studies have used comparable methods to assess individuals across a sufficiently wide age range to truly capture developmental processes (e.g., early childhood through adolescence). Here we propose a consortium of five sites (Harvard, Oxford, UCLA, University of Minnesota, Washington University), with extensive complimentary expertise in brain imaging and neural development, including many of the investigators from the adult and pilot lifespan HCP efforts. Our synergistic integration of advances from the HARVARD-MGH and WU-MINN-OXFORD HCPs with cutting edge expertise in child and adolescent brain development will enable major advances in our understanding of the normative development of human brain connectivity. The resultant unique resource will provide rich, multimodal data on several biological and cognitive constructs that are of critical importance to health and well-being across this age range and allow a wide range of investigators in the community to gain new insights about brain development and connectivity. Aim 1 will be to optimize existing HCP Lifespan Pilot project protocols on the widely available Prisma platform to respect practical constraints in studying healthy children and adolescents over a wide age range and will also collect a matched set of data on the original Skyra and proposed Prisma HCP protocols to serve as a linchpin between the past and present efforts. Aim 2 will be to collect 1500 high quality neuroimaging and associated behavioral datasets on healthy children and adolescents in the age range of 5-21, using matched protocols across sites, enabling robust characterization of age-related changes in network properties including connectivity, network integrity, response properties during tasks, and behavior. Aim 3 will be to collect and analyze longitudinal subsamples, task, and phenotypic measures that constitute intensive sub-studies of inflection points of health-relevant behavioral changes within specific developmental phases. Aim 4 will capitalize on our success in sharing data in the HCP, and use established tools, platforms and procedures to make all data publically available through the Connectome Coordinating Facility (CCF).

Project Summary This project will continue operation of the Connectome Coordination Facility (CCF) by capitalizing on the successes of the Human Connectome Project (HCP), which acquired, analyzed, and shared multimodal neuroimaging data and behavioral data on a large population of healthy adults. Major advances by the HCP include (i) the establishment of data acquisition protocols that yield high quality data across multiple modalities; (ii) the implementation of preprocessing pipelines that take full advantage of the high quality imaging data; and (iii) the establishment of a robust informatics infrastructure that has allowed widespread sharing of the HCP data within the neuroimaging and neuroscience communities. The CCF builds on these accomplishments and serves the human neuroimaging community in three ways. One aim is to provide consultation and support services to the research community for the primary purpose of harmonizing image acquisition protocols with those of the HCP. To this end, we have established a help desk whose support functions include transfer of data acquisition sequences and image reconstruction algorithms; providing updates and improvements for these sequences and algorithms; harmonization of imaging protocols and image reconstruction support for different software platforms and versions; and consultation for potential problems (e.g. image artifacts). A second aim is to provide services that maximize comparability of data acquired by CCF contributors. These services include pre-data acquisition guidance to contributors to ensure that each project?s behavioral data are obtained using HCP-compatible methods. This entails coordination with data contributors to develop and maitain mechanisms to streamline transfers of de-identified data from the study sites to the CCF database. The data from each study include the acquired images and all data associated with the project?s behavioral battery. Manual and automated quality control procedures based on existing HCP methods are executed to generate quality metrics that are published with the data. A standardized set of pipelines are then run in order to produce minimally preprocessed data that is fully harmonized with the other data sets in the CCF database. A third aim is to maintain the existing data repository infrastructure for Human Connectome Data and expand it to include connectome data from other research laboratories that are funded under the Connectomes Related to Human Diseases program. Together, these three aims enable the CCF to serve a central hub for connectomics data aggregation and harmonization. The CCF?s suite of harmonization services from data acquisition through data sharing ensure an unprecedented level of compatibility across data sets. The resulting database enables the scientific community to conduct novel analyses to better understand brain function in health and disease.