Purpose

The purpose of this Notice of Special Interest (NOSI) is to encourage new applications for developing informatics infrastructure for the Brain Behavior Quantification and Synchronization (BBQS) research program of the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative. Specifically, the NOSI supports a) creation of data archive(s) to store and manage BBQS-relevant data; b) development of computational tools or software for analyzing, visualizing and integrating BBQS-related data, and for predicting and modeling the complex dynamics of the brain-behavior system; and c) establishment of data standards or ontologies that support the BBQS-related studies.

Background

The Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative has recently launched the Brain Behavior Quantification and Synchronization (BBQS) research program. The program seeks to support the development and validation of next-gen tools, methods, and analytic approaches to precisely quantify complex behaviors and combine them with simultaneous recordings of brain activity for understanding of the complex dynamics of the brain-behavior system. The program is expected to generate large amounts of multi-modality data from multiple species, including humans. This may include videographic, audiographic, electrophysiologic, temperature and other continuous data. Some projects are also expected to generate data related to ambulation, limb movements, facial movements, eye movements, vocalizations, glandular secretion, and peripheral physiology. These data sets and related metadata are expected to be large and measured across multiple timescales.

One major challenge of the program lies in archiving and sharing these data with the community as required by both the BRAIN Initiative and NIH policies (NOT-MH-19-010, NOT-OD-21-013). Currently, there is no public data repository available from the BRAIN Initiative or other sources that are suitable for archiving and managing the BBQS-related data. To build a domain-specific archive for the BBQS-related data will be important for not only storing and sharing this domain of data, but also building a cloud-based and archive-integrated modern data ecosystem for the BBQS research. The BBQS archive is expected to collaborate with existing BRAIN Initiative informatics awards, when appropriate. Another challenge in the BBQS program is to be able to analyze and interpret the large-scale multimodal data and predict and model the complex dynamics of the brain-behavior system. This requires development and deployment of comprehensive, cutting-edge computational tools or software for data analysis, visualization and integration, as well as for machine learning (ML) and artificial intelligence (AI) to advance the research. An additional challenge in the BBQS program is to be able to ensure that the studies conducted using different technologies or approaches under different circumstances are consistent, and the outcomes are comparable and integrable. It is, therefore, essential for the BBQS consortium to develop and implement a set of common standards for (meta) data collection, description, annotation, organization and analysis. Such standards are expected to significantly enhance the interpretability, integrability and FAIRness of the data within and across the consortium.

Research Objectives

This goal of this NOSI is to support the creation of data archive(s), development of software tools, and establishment of data standards for BBQS studies to address the above-described challenges in the research program. The informatics infrastructure and tools to be developed under this NOSI are expected to be widely used by BBQS investigators, as well as by a broader community. Applications in response to this NOSI should therefore justify the importance and implications of the proposed informatics infrastructure or tools to the BBQS program, and identify the potential user base. The projects supported under this NOSI are expected to support, communicate and collaborate with the funded BBQS research projects. Applicants should familiarize themselves with the BBQS research program and funded projects (https://www.braininitiative.nih.gov/funding/initiatives.htm; also see RFA-MH-23-335 and RFA-DA-23-030).

The specific goals of this NOSI are:

1. Development of data archive(s) to focus on either the creation of a new or continued development of an established data repository for BBQS-relevant data. The proposed archive should use state-of-the-art and cost-effective technologies and approaches and is of high value to the broad brain-behavior research community. The archive should implement a cloud-based computational platform with relevant analytics tools and data standards to build a modern data ecosystem for BBQS-related studies.
2. Development of computational tools or software. The topics of the development include, but are not limited to:

1. Capture, quantify and synchronize behaviors within a complex dynamic environment.
2. Align or link behavior data with simultaneously recorded neural activity, or map relationships between behaviors and multimodal sensory inputs, or between behaviors and environment, across multiple timescales.
3. Decipher behavioral dynamics or unravel brain-behavior relationships to study “the brain in action".
4. Support ML/AI applications in signal extraction, encoding/decoding models, movement analysis, generative modeling, decision-making, and controls, among others.
5. Enable cross-modality, cross-scale, and cross-species data integration.
6. Enable pattern and trend identification, data visualization, and dataflow management.
7. Support big data approaches to BBQS-related studies.

3. Development of data standards and relevant ontologies. Applications should develop community standards or ontologies, which should be clearly linked to broad use cases of the BBQS research. The ontologies should be domain-specific, capturing various brain-behavior knowledge areas.

The BRAIN BBQS research program is particularly interested in applications from multi-disciplinary teams that, in addition to expertise in data sciences and informatics, also include diverse expertise in behavioral science, including but not limited to behavioral, cognitive and systems neuroscience, neuroethology, biomechanics, psychology and psychiatry, as well as computational neuroscience.