Current research projects and methods have demonstrated a need for new strategies and tools to produce brain models that represent brain structure and function. These models would allow for brain research to explore questions of health and disease in large populations, different disease states, across imaging modalities and beyond the demographic boundaries of age, sex and species. LONIR furthers this mission by developing new techniques to investigate brain structure and function in their full, multidimensional complexity.

Building strong collaborative relationships is vital to the advancement of brain research. LONIR grants researchers access to international networks of collaborators with a diverse array of tools to create, analyze, visualize, and interact with models of the brain. Projects have been selected that address the fields of Technology, Research and Development (TR&D).

Research Areas:

Data Sciences focuses on the methodological developments for the analysis of brain imagery. Specifically, this project will design and distribute new methods for robust image segmentation and registration, quality assurance and evaluation of image processing results, and processing of structural and diffusion brain data.

Connectomics will advance the study of brain connectivity using diffusion imaging and its powerful extensions. This project will go beyond tensor models of diffusion for assessing fiber integrity and connectivity, develop tract-based statistical analysis tools, introduce novel connectivity mapping approaches, and provide mechanisms for studying the genetics of brain connectivity.

Intrinsic Shape Analysis will allow the robust and accurate comparison of structural variations in development and pathology across population.TR&D 3 is tightly related to TR&D 1 and 2. For TR&D 1, this project will provide robust tools for the large scale study and organization of the shape representation of anatomical structures.

Current Research

The brain modeling approaches targeted by LONIR focus on new strategies for surface and volume parameterization that provide an advanced analysis of surface and volumetric brain models, tracking their change across time. Additional research cores include anatomic fundamentals and analyzing anatomic and cytoarchitectural attributes across multiple scales and time.

LONIR also has a core that focuses on visualization and animation, for the dissemination of brain models that visualize complex variations in brain structure and function across time. This includes projects for handling cortical data that are in development.

Current research is also being conducted by ongoing national and international collaborations that are analyzing normal and aberrant growth processes, brain development, tumor growth, Alzheimer’s disease and related degenerative disease processes, schizophrenia, and brain structure in normal and diseased twins.


The approach to integrated computational neuroscience is based on a scalable, portable, and distributed infrastructure, which uses object-oriented programming, Extensible Markup Language (XML), encrypted distributed computing and open-source design, implementation, and tool dissemination. Algorithms are designed to generate average models of brain anatomy and maps of growth, degeneration, and their population statistics. These models are based on parametric surfaces, volumetric morphology, and topology-preserving mapping. The resulting algorithms are implemented, validated, and distributed via the LONIR Pipeline environment and are applicable to a variety of computational neuroscience challenges in normal brain and disease.