# BBQS AI Resource and Data Coordinating Center (BARD.CC)

> **NIH NIH U24** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2024 · $1,993,419

## Abstract

SUMMARY
Understanding the complex relationship between brain activity and behavior is one of the most exciting and
challenging pursuits in neuroscience. The proposed BBQS AI Resource and Data Coordinating Center
(BARD.CC) aims to facilitate innovative research in this area by managing, sharing, and harnessing the power
of vast amounts of data and machine learning resources generated by various projects within the BBQS
consortium. We will focus on five interrelated aims: 1) Data Management; 2) Data Standards; 3) Machine
Learning and Artificial Intelligence (ML/AI) Resources; 4) Data Ecosystem; and 5) Dissemination, Training, and
Coordination. The first aim is to serve as a hub for efficient data curation, management, and sharing. We will
collaborate with other BBQS projects and coordinate with existing BRAIN data archives to curate and
harmonize project data. Data management will be handled by a combination of automated data ingestion and
human oversight, transitioning to a fully automated system over time. We will work with scientists and relevant
communities to implement robust quality assurance and control solutions. The second aim focuses on
establishing data standards for novel sensors and multimodal data integration, as informed by the use of
existing standards and best practices from similar efforts. We will aggregate relevant standards for data and
metadata, data processing methods, appropriate ontologies, and common data elements, and adapt as
needed for evolving methodologies. The third aim involves the development and definition of ML/AI resources
for BBQS. We will evaluate and curate relevant ML/AI models and platforms, aggregating datasets, models,
and other ML/AI resources from both within and outside the BBQS consortium. These resources will be made
available to consortium members, with each resource's origin documented and evaluated for performance and
ethical generation and use. Moreover, all models will be made available through public repositories, allowing
for widespread access and utilization. The fourth aim involves creating a cloud-based data ecosystem and
computational platform. We will collaborate with relevant archives and computing facilities to develop a
computational platform in the cloud. This platform will enable access to and processing of even very large data
sets with commonly used pipelines and provide a wide range of users, even those with limited resources, with
computational capability to analyze and visualize data, models, and model outputs. Finally, the fifth aim is
centered around efficient dissemination, training, and coordination of BBQS research resources. We will
coordinate data sharing, offer training on relevant topics like neuroinformatics, neuroethics, and ML/AI, and
maintain a consortium Web portal. Furthermore, center staff will coordinate consortium activities like meetings,
working groups, and policy and ethics discussions, ensuring smooth and effective operation. In summary,
BARD.CC aims to cat...

## Key facts

- **NIH application ID:** 10888562
- **Project number:** 1U24MH136628-01
- **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Laura Yenisa Cabrera Trujillo
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,993,419
- **Award type:** 1
- **Project period:** 2024-08-19 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10888562

## Citation

> US National Institutes of Health, RePORTER application 10888562, BBQS AI Resource and Data Coordinating Center (BARD.CC) (1U24MH136628-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10888562. Licensed CC0.

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