Staff for the Functional Brain Imaging Laboratory. Back row, left to right: An Vo, Shichun Peng, Chris Tang. Front row: Yilong Ma, Patricia J. Allen. David Eidelberg, Vijay Dhawan, and Phoebe Spetsieris are missing from the picture.

The Functional Brain Imaging Laboratory

The Functional Brain Imaging Laboratory (FBIL) is directed by Dr. David Eidelberg, and is situated within the Center for Neurosciences of The Feinstein Institute for Medical Research. The laboratory occupies 4,000 square feet on the fourth floor of the Feinstein building. Neuroscience research activities in the laboratory are supported by two biophysicists (Drs. Vijay Dhawan, and Yilong Ma) with extensive knowledge of brain imaging techniques, two computer scientist/programmers (Drs. Phoebe Spetsieris and Shichun Peng) with expertise in biomedical computing, and a senior data analyst/biostatistician (Dr. Chris Tang). This professional staff supports the research activities of eight full-time neuroscience investigators as well as an equal number of postdoctoral fellows and graduate students. The laboratory staff develops and implements a wide variety of innovative approaches to the acquisition, processing, and analysis of multimodal brain images from human subjects and animal models.

In addition to the ongoing research activities of the scientific staff, FBIL supports the research needs of investigators from other Centers within The Feinstein Institute for Medical Research.

Specific services include:

  • Consulting about the design of neuroimaging protocols for patient-oriented research;
  • Facilitating access to the PET and MR scanners for investigators who want to perform imaging experiments;
  • Helping to process and analyze PET data. Data analysis entails the implementation of image functionalization, PET/MRI co-registration algorithms, the implementation of segmentation algorithms, atrophy correction, region-of-interest (ROI) placement, and voxel-based statistical analyses;
  • Helping to process and analyze MR data, including the creation of delineation criteria for manual ROI measurements, and distortion correction and image registration of diffusion tensor images;
  • Supporting bioinformatics for imaging studies, as well as informal consulting on bioinformatics questions by other investigators. FBIL also provides training in specialized techniques to faculty of The Feinstein Institute for Medical Research, as well as to staff of the clinical departments of the North Shore-LIJ Health System, to postdoctoral students and fellows, and to graduate students;
  • Training in the use of PET for assessing cerebral metabolism, hemodynamics, and neurotransmitter function, as well as for the study of activation responses during task performance; and
  • Training in the use of MRI for high-resolution, anatomical imaging (including voxel-based morphology—VBM—and diffusion tensor imaging—DTI), as well as for functional mapping (with blood oxygenation level dependent—BOLD—imaging and perfusion imaging techniques).

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Data Analysis and Bioinformatics:

Three staff members—a biophysicist with extensive experience in brain imaging analysis, a senior programmer with expertise in biomedical computing, and a data manager—manage FBIL’s bioinformatics and computing infrastructure. Members of the laboratory have developed and implemented a wide variety of innovative approaches to the visualization and analysis of PET and MRI images. In addition to providing technical consultation to investigators using our facilities, the group supports ongoing research through its long-term commitment to integrate database and analytical routines on a single common computing platform.


Computing Environment:

The computing facility encompasses a large number of PCs running Windows 7 operating systems, all capable of accessing the central database via the local intranet. Standard software packages, such as SPSS and SAS, are available to perform statistical analyses. A dedicated state-of-the-art 64-bit high-performance Windows cluster system has been purchased for data archival and image analysis. The system can perform multi-core processing, data mining, and redundancy backup to the level of industrial standards.


Analytic techniques:

Several state-of-the-art tools are available to analyze PET and MRI brain images, both on a regional and a voxel basis using a series of the state-of-art approaches. In-house software tools (ScAnVP) incorporate methods for quantifying cerebral blood flow, glucose metabolism, neuroreceptor binding, and MRI data, as well as custom-built methods for spatial covariance mapping, all available on the Downloads page. The laboratory also routinely relies on third-party programs for applying such techniques as statistical parametric mapping (SPM) ( and FMRIB Software Library (FSL) ( FBIL is currently optimizing new multivariate tools, including algorithms for supervised principal component analysis (PCA) and independent component analysis (ICA)—which will provide FBIL users with a full battery of solutions to multivariate image analysis.



The key database task for FBIL is storing brain images acquired from ongoing PET and MRI studies. The images are transferred to the laboratory regularly from PET and MRI scanners through the local area network (LAN) of the North Shore-LIJ Health System. A secure FTP server is also available for electronic image transfer from other collaborating medical centers. The scans are then inspected as part of the quality-control program, archived on the computer server, and entered into the database along with the corresponding experimental, clinical, and behavioral information. Databases keep track of preprocessed scans and outcome measures of brain images generated by our research projects.

A centralized SQL database management environment supports all research studies done at FBIL, using Microsoft SQL Server 2005 and MS Access. This database environment makes it possible to:

  • get real-time updates of the information system, one of the largest clinical and imaging databases in the world on patients with Parkinson’s disease and related disorders;
  • create and maintain the extensive clinical and scientific database, continually generated as part of ongoing projects; and
  • expand its own capability by sharing and exchanging data with other laboratories.

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