# GIFTwrap: a containerized and FAIR cloud-based implementation of the widely used GIFT toolbox: Request for supplemental funds for NIH 2R01EB006841 “Multivariate methods for identifying multi-task/mult

> **NIH NIH R01** · GEORGIA STATE UNIVERSITY · 2021 · $233,367

## Abstract

Abstract
The GIFT software was the first software tool to implement ICA of fMRI data and group ICA which has since
been widely adopted by the brain imaging community. This tool has continuously expanded over the years, now
providing access to a large suite of tools including data-driven functional connectivity, over a dozen different ICA
approaches, independent vector analysis, dynamic functional connectivity, spatial dynamics, connectome visu-
alization, and much more that are not offered in any other single tool. It also offers fully automated ICA ap-
proaches for use in individual subject prediction and classification. Though we have begun to evolve the model,
GIFT is primarily still based on a standalone software development and analysis model. Modern tools have
moved towards centralized analysis, comparability, analytic interaction and community development. In this sup-
plement we will focus on three main goals: 1) Building of architecture improvements to facilitate FAIR principles
and modernize the tools, 2) to release the GIFT tools as a brain imaging data structure app (BIDSapp) for easy
use and integration into modern analysis frameworks, and to deploy GIFT in several widely used analytic plat-
forms, and 3) to provide a web-based interface for individuals to run fully automated ICA analysis which requires
a simple upload of data to the tools. The result will have significant impact as it will offer a large expansion of
utility for a tool which already has a large user base, will open up its use to many more in the community including
those focused on big data tools and deployment within a modern containerized environment, and will facilitate
automation, replication, cross-study comparisons, and robustness to processing pipelines and noise via spatially
constrained ICA and automated labelling of intrinsic networks (beyond just artifact versus signal).

## Key facts

- **NIH application ID:** 10406750
- **Project number:** 3R01EB006841-15S1
- **Recipient organization:** GEORGIA STATE UNIVERSITY
- **Principal Investigator:** VINCE D CALHOUN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $233,367
- **Award type:** 3
- **Project period:** 2007-04-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10406750

## Citation

> US National Institutes of Health, RePORTER application 10406750, GIFTwrap: a containerized and FAIR cloud-based implementation of the widely used GIFT toolbox: Request for supplemental funds for NIH 2R01EB006841 “Multivariate methods for identifying multi-task/mult (3R01EB006841-15S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10406750. Licensed CC0.

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