This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.The development of high dimensional brain mapping in the field of computational anatomy (CA)and its integration with other state-of-the-art brain imaging technologies continues to be a uniqueopportunity to study both the underlying neurobiology of brain structure and its connections, and therelationships between brain structure abnormalities and patterns of cognitive deficits. Such mappingtools permit the precise formulation of hypotheses concerning brain structure and function determinedby patterns of connectivity and shape particularly in development and neurodegeneration.Over the past fifteen years, many investigators have been studying the shape and structure of thehuman brain in multiple anatomies in common coordinates (e.g.8, 33, 39, 41, 42, 61, 63, 65, 80, 88,90, 101, 136, 151, 152). Further, emerging methodologies that integrate anatomical and functionalinformation from multiple data provide an opportunity to ask detailed anatomical questions in a singleset of standard coordinates. It is now possible to perform functional measurements and anatomicalmeasurements at roughly 1.0 mm resolution. Systems now exist in isolation of each other forexamining gray matter reconstructions of the neocortex, studying the gyrification, folding and sulcalpatterning of the gray/white boundary of the neocortex, as well as the anatomical size and shape ofdeep nuclei in the brain such as the hippocampus, thalamus and caudate.Our own group has been involved in the development of these tools, including surface and volumemapping tools, cortical and surface generation tools, gyral and sulcal curve generation and theanalysis of these structural data. Designed and developed in the 1st grant period, these methods arenow being used by investigators around the world in structural studies of the neocortex and deepnuclei in a variety of neurodevelopmental and neurodegenerative processes.Recent developments in observing the activation of brain regions via functional magneticresonance imagery (fMRI) while different tasks are being processed are now providing a clear look atthe working of this marvellous machinery. Such studies are expected to reveal an in depthunderstanding of the intricate and effortless processing humans can perform while they go about intheir daily lives. Knowledge gained from such studies is expected to provide better understanding ofthe normal mechanisms and aberrations to these mechanisms in developmental situations.Furthermore, diffusion tensor magnetic resonance imaging (DT-MRI or DTI) provides usefulphysiological information noninvasively, not only about the fiber structure of normal tissue, but alsoabout its changes in development, disease and degeneration. It has already been shown to be ofvalue in studies of neuroanatomy, fiber connectivity, and brain development. DT-MRI has been usedin the investigation of cerebral ischemia, brain maturation and traumatic brain injury. It also promisesto further our understanding of brain disorders and abnormalities such as stroke, tumors andmetabolic disorders, epilepsy, multiple sclerosis, schizophrenia, Alzheimer's disease and cognitiveimpairment.Our collaborators have now begun to use fMRI and DT-MRI data to understand the intricatefunctional properties of the whole brain as well as the neocortex. To this end, the aims of TRD4 are toextend previously developed CA tools for the neocortex to the whole brain and develop additional CAtools for analyzing functional and connectivity data in brain and cortical structures. The tools will bemade available to the wider scientific community. In particular, the proposed developments shouldbenefit a wide range of clinical disciplines from psychiatry to pediatrics including those funded by thefollowing NIH grants:1. developmental disability (Denckla, Mostofsky, Cutting, Scarborough, Naidu) - performfunctional and longitudinal analysis of cognitive processes on frontal lobe, basal ganglia andsubcortical regions associated with developmental disability (Aims 1, 4, 5)2. attention and memory (Yantis, Stark and Courtney-Faruqee) perform structural andfunctional analysis of cognitive processes on hippocampus and associated cortical surfacesimplicated in attention and memory (Aims 1, 4, 5)3. neurodegeneration/dementia (Albert, Csernansky, Reading) - perform structural and functionalanalysis of stages of neurodegeneration associated with the hippocampus, caudate, cingulate,parahippocampal gyrus, prefrontal cortex as well as gyral and sulcal folds of these structures(Aims 1, 4, 5), and co-register neuronal connections (Aims 2,3)4. pediatric ischemia/trauma (Graham, Hoon, Christensen, Levin) - perform structural andfunctional analysis of stages of neurodegeneration associated with white matter tracts andstructures (Aims 1, 4, 5), and co-register neuronal connections (Aims 2,3) during growth5. Stroke (Hillis) - perform structural and functional analysis of developmental stages of neuronaldiseases (Aims 1, 4, 5), and co-register neuronal connections (Aims 2, 3)6. pediatric brain tumors (Horska) - perform structural and functional analysis of stages ofneurodegeneration associated with white matter tracts and structures (Aims 1, 4, 5), and coregisterneuronal connections (Aims 2,3) during growth7. depression and mood disorders (Botteron, Pearlson) perform structural and functionalanalysis of developmental stages of diseases associated with the prefrontal cortex andhippocampus as well as gyral and sulcal folds of these structures (Aims 1, 4, 5); co-registerneuronal connections between substructures (Aims 3, 4).8. biomedical informatics (Rosen) perform large scale multi-site shape analysis of brainstructures and substructures (Aims 1, 4, 5) and of neuronal connections (Aims 2, 3)Our specific aims are to integrate such structural and functional analysis tools into a softwaresystem by developing the following algorithms:
Aim 1 : Large Deformation Diffeomorphic Metric Mapping (LDDMM) for landmarks, curves, surfacesand volumes in whole brain analysis and registration;
Aim 2 : LDDMM for Diffusion Tensor images (LDDMM-DT) and tensor algebra;
Aim 3 : LDDMM for longitudinal and developmental analysis;
Aim 4 : LDDMM and signal processing methods for Functional AnatomyBuilding a software system that supports the data structures of curves, surfaces, and scalar andtensorial lattices of volumes will be essential in utilizing methods developed in TRD1 and TRD3 instudying brain structure and function.
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