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STTR Phase I: fMRI Dynamic Phantom for Improved Detection of Resting-State Brain Networks

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 1622525
Agency Tracking Number: 1622525
Amount: $225,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: BM
Solicitation Number: N/A
Timeline
Solicitation Year: 2015
Award Year: 2016
Award Start Date (Proposal Award Date): 2016-07-01
Award End Date (Contract End Date): 2017-06-30
Small Business Information
60 Marine Street
Farmingdale, NY 11735
United States
DUNS: 154815534
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Alan Kriegstein
 (631) 393-6401
 alank@alascience.com
Business Contact
 Alan Kriegstein
Phone: (631) 393-6401
Email: alank@alascience.com
Research Institution
 State University of New York at Stony Brook
 Lilianne Mujica-Parodi
 
Stony Brook University
Stonybrook, NY 11794
United States

 Nonprofit College or University
Abstract

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to dramatically improve the detection sensitivity of resting-state fMRI. In recent years, large-scale ($150M- $1.2B USD) and long-term (10-12 year) international investments (e.g., NIH Human Connectome Project, White House BRAIN Initiative, UK Biobank, EU Human Brain Project) have expanded the reach of human fMRI to include faster pulse sequences and more complex analytic tools, higher field strength, integration with multi-scale experiments and modeling, and an emphasis on integration of data across multiple scanner/study sites. This generation of fMRI studies goes beyond the original simplistic models that focused upon activation maps, to investigate connections, networks, and dynamic nonlinear circuits in the brain. New ways of thinking are being applied to some of our highest-impact areas of societal interest, ranging from clinical depression, addiction, autism, and brain injury, to age-based cognitive degeneration. However, while fMRI research dramatically accelerates, quality assurance protocols for the MRI machines needed to generate these findings have lagged far behind, relying upon static phantom protocols no longer fully capable of targeting quality control issues relevant to current and emerging applications. The Stony Brook Dynamic Phantom is designed to address this urgent need. The proposed project builds upon a 1st generation working prototype of the dynamic phantom (patent pending), to develop engineering improvements in the 2nd generation prototype necessary to increase its durability and reliability in preparation for commercialization. The six objectives addressed in Phase I are associated with increasing precision, accuracy, reliability/reproducibility, and usability from the perspectives of both the phantom's hardware and software.

* Information listed above is at the time of submission. *

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