This wiki page supports the BRAIN Initiative Brain Behavior Quantification and Synchronization program.
Workshop on Brain Behavior Quantification and Synchronization: Sensor Technologies to Capture the Complexity of Behavior
The goals of this workshop include the following:
- An introduction to the types and fabrication of sensors and sensing networks
- Multi-sensor integration for tracking movement; ethical, comparative, and developmental focus
- Integration of sensor information with other data streams, including brain recordings where possible, to capture naturalistic behavior
Data standardization, archiving, security, and privacy
- Featured experiments and development of computational models
- National Institute of Mental Health
- National Institutes of Health’s Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative
This event is free and registration is required. Onsite registration is available, but if attendees want lunch, you must register in advance.
The two BRAIN Initiative 2.0 reports ("The BRAIN Initiative 2.0: From Cells to Circuits, Toward Cures" and "The BRAIN Initiative and Neuroethics: Enabling and Enhancing Neuroscience Advances for Society") highlight that a critical step forward is to study “the brain in action,” including efforts to develop “tools to analyze naturalistic (untrained) and trained behaviors” and “to assimilate and link brain recordings with behavior” (p. 34 of "The BRAIN Initiative 2.0: From Cells to Circuits, Toward Cures"). Matching the scientific rigor and precision of measurements of brain activity with equally precise, temporally dense measurements of the functional output of the brain, as expressed in a broad range of behaviors, will accelerate the discovery of brain-behavior relationships in both health and disease. Achieving a comprehensive understanding across these levels of analysis demands the same level of rigor, precision of measurement, and temporal resolution across all levels.
At present, tools for measuring behavior in humans and other species lack the necessary precision and resolution to fully capture behavioral dynamics synchronously with data from the environment with which the organism is interacting and which shapes the behavior under study. To address this gap, the BRAIN Initiative BBQS funding opportunities support 1) development of tools for simultaneous, multimodal measurement of behavior within complex, dynamic physical and/or social environments and align these data with simultaneously-recorded neural activity; and 2) development of novel conceptual and computational models that capture dynamic behavior-environment relationships across multiple timescales and that can integrate correlated neural activity into the model. Potential applicants and others interested are encouraged to visit the NIH BRAIN Initiative website for information and guidance https://www.braininitiative.nih.gov/funding/initiatives.htm.
BRAIN Initiative: Brain Behavior Quantification and Synchronization – Data Coordination and Artificial Intelligence Center (U24 Clinical Trial Optional) RFA-MH-23-130
BBQS Data Coordination and Artificial Intelligence Center (DCAIC)
The BBQS research program is characterized by certain features and challenges that need to be addressed through the creation of a multi-component, cross-discipline Data Coordination and Artificial Intelligence Center (DCAIC). First, the BBQS program will generate large amounts of multi-modality data from multiple species, including humans. This may include videographic, audiographic, electrophysiologic, temperature, and other continuous data. In addition, some projects are 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 in size and measured across multiple timescales. All the data will be deposited into relevant BRAIN data archive(s) to share with the community as required by the BRAIN Initiative and NIH data sharing policies (NOT-MH-19-010, NOT-OD-21-013). To manage such massive and diverse data, and to prepare the data for archiving, will be challenging. The necessary expertise includes both knowledge about how the data were measured along with access to appropriate computational and informatics tools and infrastructure. Often, individual laboratories do not have all of the needed knowledge or infrastructure. The DCAIC should be envisioned as providing a more cost/administration-efficient and process-consistent solution for such large-scale data management and preparation for archiving.
The BBQS projects will employ diverse technologies and approaches to measure and collect research data under different circumstances. It is, therefore, essential to adopt a common set of standards in the (meta)data collection, description, annotation, organization, and analysis in order to ensure consistency across different studies and to make the outcomes comparable and integrable. The DCAIC will be responsible for establishing such standards across the BBQS program through a centralized coordination effort. This will be accomplished by working together with other BBQS projects and relevant BRAIN data standards projects, with inputs from the research community and consensus from the BBQS consortium. The established standards will be of great value in strengthening data interpretability and integrability within and across the consortium, while facilitating the compliance of BBQS data with the FAIR (Findable, Accessible, Interoperable and Reusable) principles.
The BBQS program will employ a great amount of machine learning (ML) and artificial intelligence (AI) approaches in the research, which is expected to range from mapping data streams of behavior as a multidimensional response to neuronal activity, to building new conceptual models of behavioral systems, to predicting behavior that might guide intervention development or selection. It will be important for the BBQS consortium to develop a comprehensive set of ML/AI research resources. The resources will include ML/AI-ready datasets and training data, validated models, best AI practices, among others, specific to the studies. These resources will enable scientists to quickly build on and extend the results of others, and compare new experiments to state-of-the-art practices while strengthening the research rigor and reproducibility. Developing or preparing such comprehensive ML/AI resources is highly time-consuming and costly; a centralized effort by the DCAIC will be more efficient and avoid considerable duplicative efforts.
Last but not least, the BBQS program will involve extensive data processing, analysis and modeling, and large-scale computation. It will be necessary for the consortium to develop a cloud-based computational platform that is integrated with the data repository under the same set of data standards. Such an integrated data ecosystem is expected to significantly enhance analytic capability and data reusability. The ecosystem will also promote a collaborative and consistent research environment, making scientific discovery more robust and reproducible. The ecosystem will nevertheless provide a valuable learning and working environment for students and citizen scientists.
The NOFO will support a single award to a multi-disciplinary team with a single or multiple PIs to create the DCAIC. Activities directed by the DCAIC will fall into five interrelated categories:1) Data Management; 2) Data Standards; 3) ML/AI Resources; 4) Data Ecosystem; and 5) Dissemination, Training, and Coordination. Each application in response to this NOFO must address all five categories of research activities.
The DCAIC is expected to support, communicate, coordinate and collaborate with the other BBQS projects on each category of research activities. As part of this process, the DCAIC will also solicit input from various fields contributing to the behavioral and neural sciences to guide design and implementation of DCAIC components. The DCAIC is also expected to collaborate or integrate with relevant BRAIN informatics infrastructure projects, particularly data archive(s). Applicants should therefore familiarize themselves with the BBQS program (www.braininitiative.nih.gov/funding/initiatives.htm; also see the NOFOs RFA-MH-22-240 and RFA-DA-23-030), as well as the BRAIN Informatics Program (www.braininitiative.nih.gov/brain-programs/informatic; also see the NOFOs RFA-MH-20-600, RFA-MH-22-145, RFA-MH-21-135), in preparation of the application.
The DCAIC team should be multidisciplinary and is required to include scientists that contribute, specifically, broad and deep expertise in research design and analysis of high-dimensional and/or multimodal behavioral data, and expertise in collection and analysis and of high-dimensional neural data. The PD(s)/PI(s) of the DCAIC must be experienced in the coordination and management of multiple projects.
See Full NOFO at: https://grants.nih.gov/grants/guide/rfa-files/RFA-MH-23-130.html
Notice of Special Interest (NOSI): BRAIN Initiative: Developing Data Archive, Informatics Tools and Data Standards for Brain Behavior Quantification and Synchronization (BBQS) NOT-MH-23-115
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.
For the full notice see NOT-MH-23-115
BRAIN issues a new funding opportunity for the development of technologies to understand behavior at the organismal level
This funding opportunity, with the next due date of February 14, 2023, is part of the Brain-Behavior Quantification and Synchronization (BBQS) program. It will support the development of research projects aimed at advancing approaches for high-resolution synchronized capture of complex behavioral and environmental data and development of computational models of behavior as a complex dynamic system.
The National Institutes of Health (NIH) recently issued the funding opportunity announcement (FOA) BRAIN Initiative: Brain-Behavior Quantification and Synchronization (BBQS) – Transformative and Integrative Models of Behavior at the Organismal Level (R34 Clinical Trial Not Allowed) [RFA-DA-23-030]. This BBQS funding opportunity will support planning activities that will lay the groundwork for a scientific project aimed at 1) integrating and advancing approaches for high-resolution capture of multiple dimensions of behavior at the organismal level, as well as dynamic features of the organism’s environment and 2) developing computational approaches that integrate multidimensional behavioral and environmental data across multiple time scales with the aim of modeling behavior as a complex dynamic system.
BRAIN issues new funding opportunity for the development of cutting-edge tools to understand the neural basis of behavior in humans
Since 2014, The BRAIN Initiative® has aimed to accelerate the development and application of innovative neurotechnologies that enable researchers to understand the human brain. A major gap in our understanding of the human brain is a paucity of tools to better link patterns of neural activity to patterns of behavior. Establishing a clearer causal link between neural activity and behavior will ultimately lead to new ways to treat and prevent brain disorders.
The National Institutes of Health recently issued the BRAIN Initiative: Brain Behavior Quantification and Synchronization (BBQS) (R61/R33 Clinical Trial Optional) [RFA-MH-23-335] to support the development of cutting-edge tools for simultaneous, multimodal measurement of behavior within complex environments and integration of these tools with simultaneously recorded brain activity in humans.