Funded Awards

Dr. Ecker's group will use signatures of epigenetics, the switching on-and-off of genes in response to experience, in mouse frontal cortex to help identify different classes of cells and understand their function.

A thorough understanding of the complexities of the brain’s different cell types requires the sharing and integration of myriad genomic information generated from various data sources. Owen White proposes creating a Neuroscience Multi-Omic (NeMO) Archive, a cloud-based data repository for -omic data. White and his team of researchers will establish an archive for multi-omic data and metadata of the BRAIN Initiative. The group will document and archive data processing workflows to ensure standardization, as well as create resources for user engagement and data visualization. The NeMO Archive will provide an accessible community resource for raw -omics data and for other BRAIN Initiative project data, making them available for computation by the general research community.

Identifying individual cell types in the brain is a monumental task that is complicated by the limitations of current molecular technologies. To measure genetic diversity in the whole mouse brain, Huang and Arlotta will lead a team using next-generation droplet-based single-cell transcriptome sequencing along with other highly sensitive single-cell techniques that allow for high-throughput data collection. They plan to map these data onto the spatial locations of forebrain neurons with the help of high-resolution microscopy and genetically driven cell markers. These efforts will provide the scientific community with unprecedented detail about neurons’ molecular and spatial characteristics that can be used to develop additional tools for cell-specific manipulations.

The large number of cells in the brain and the complexity of their molecular and functional characteristics make it difficult to define individual cell types. Zeng and colleagues plan to complement high throughput droplet-based transcriptome survey with deep sequencing technique and multiplexed error-robust fluorescence in situ hybridization (MERFISH) to comprehensively characterize gene expression information from anatomically mapped cells across the entire mouse brain. Additionally, they will use patch clamp method to measure neuronal function in specific brain regions, and combine electrophysiological with transcriptomic and morphological information to provide integrative profiles of individual cell types. These efforts will refine how we define cell types and will produce a census of individual cells in the mouse brain that can then be targeted for further study.

Advances in microscopy and imaging have created new possibilities in many fields of research, but these advances have also generated large amounts of data that can overwhelm traditional data management systems. Along with collaborators at Carnegie Mellon University and the University of Pittsburgh, Alexander Ropelewski plans to establish a BRAIN Imaging Archive that takes advantages of infrastructure and personnel resources at the Pittsburgh Supercomputing Center. The Archive will include a pipeline for data submission, user access and support, and BRAIN Initiative community engagement through an online presence, workshops, and hackathons. This unique resource will provide an accessible and cost-effective way for the research community to analyze, share, and interact with large image datasets of the BRAIN Initiative.

Connectomics describes a field of study that builds maps of the connections within the brain. Dr. Lichtman and colleagues have developed a facility for generating high-resolution, large-volume serial section electron microscopy data that can be used to generate connectomic maps. In this project, access to the facility, techniques, and analytical software will be provided to the broader neuroscience community. This will allow other research groups who may be inexperienced in these techniques to generate data in projects aimed at mapping brain circuitry, a high priority goal in the BRAIN 2025 report. By providing this resource, Dr. Lichtman and colleagues will help researchers classify the cell types within healthy and diseased brains or model systems, which will improve our understanding of brain function and neurological disorders.

The community’s need for an integrated open-source analysis platform is rapidly growing due to the increasing capacity of extracellular electrodes and the limited number of new and validated spike- sorting methods. JRCLUST, a free, open-source, standalone spike sorting software, offers a scalable, automated and well-validated spike sorting workflow for analysis of data generated by large multielectrode arrays. The software can tolerate experimental recording conditions from behaving animals, and it can handle a wide range of datasets using a set of pre-optimized parameters making it practical for wide use in the community. JRCLUST has been adopted in 20+ labs worldwide since its inception less than a year ago. Drs. Kimmel and Nathan seek to expand and maintain JRCLUST, thus empowering researchers to elucidate how functionally defined subpopulations of neurons mediate specific information-processing functions at key moments during behavior.

To understand how the activation of individual neurons in the brain leads to particular behaviors, it is necessary to identify synaptic connections to downstream neurons. Although considerable information about neuronal circuits has been generated using rabies virus to trace trans-synaptic connections in the retrograde direction, there is no comparable technique for trans-synaptic tracing in the anterograde direction. In rodent brains, Arnold and colleagues will optimize a non-toxic method for anterograde monosynaptic tracing from single neurons to virtually any postsynaptic receptor. Their method labels only active synapses, ensuring the technique’s physiological relevance.

Deep brain stimulation (DBS), a method of modulating brain circuit function, is FDA-approved for certain brain disorders such as Parkinson’s Disease. The NIH BRAIN Initiative aims to launch neurotechnological developments that include new ways of directly affecting brain circuit function. Use of these novel interventions warrants careful consideration about ways in which brain stimulation may affect personal identity, autonomy, authenticity and, more generally, agency. In this project, Dr. Roskies and her team will develop an assessment tool to measure changes in agency due to direct brain interventions, and establish a database to catalogue these changes in agency in various patient populations receiving DBS. These efforts have the potential to facilitate improvements in therapeutic approaches and informed consent and will be used to develop a framework for further neuroethical thought about brain interventions, allowing us to better identify, articulate, and measure effects on agency.

To understand brain function, we need to be able to able to monitor cellular activity in the brain noninvasively over time.  To overcome these limitations Dr. Sayler's group will develop a set of self-exciting, continuously bioluminescent, optical imaging reporters that, unlike existing systems, are pre-engineered to support genetically encoded, autonomous, metabolically-neutral, neuron- or astrocyte-specific fluorescence that can be monitored with common laboratory equipment.

The proliferation and heterogeneity of magnetic resonance imaging (MRI) experiments, data analysis pipelines, and statistical modeling procedures presents a challenge for effective data sharing and collaboration. Russell Poldrack and colleagues propose expansion of the Brain Imaging Data Structure (BIDS), which standardizes the description and collection of imaging data/metadata for MRI, with development plans for other neuroimaging types as well. Under BIDS, the group will develop standards for pre-processing data pipelines, computational modeling results, and statistical modeling, using quick validation of any implemented standard so that researchers can assess whether their data fit within BIDS guidelines. These standardization goals will facilitate sharing of data, modeling, and results, ensuring their usability and engaging the greater research community in developing highly useable data standards.

Technological advancements in high-resolution imaging of brain volumes permits the accumulation of huge quantities of data that requires solution for storage and archiving. Dr. Brock’s project develops an open, accessible, and cloud-based data archive for electron microscopy and X-ray microtomography data by leveraging the proven architecture of the existing BossDB database. Allowing for petabyte scale data storage, curation, sharing, visualization and analysis, the archive is scalable and allows for a fast in- memory spatial data store, seamless migration of data between low cost and durable object storage (i.e. S3), and rapid access to the enormous datasets. The system enables computing data quality metrics on large datasets and metadata stores through a standardized interface. The archive is developed through an agile process that actively folds in community stakeholders for regular reviews and continuous opportunities for design input.

AFNI (Analysis of Functional NeuroImages) is an open-source software package for neuroimaging analysis and visualization of both functional and structural MRI as well as other modalities. Drs. Cox and Nielson propose to extend this widely used software package by offering containerization, cloud accessibility and web-accessible visualization. The software extension could support evolving BRAIN Initiative standards for human neuroimaging data organization and experiment specification. The project makes it possible for public integration testing of the software package, thus enabling end-user feedback and wider adoption and dissemination within the neuroimaging community.

Different neurons show widely varying patterns of gene expression and widely varying patterns of electrical spiking. It is not currently possible to predict the electrical spiking properties of a cell from its pattern of gene expression. Cohen’s team seeks to develop tools to record gene expression and spiking patterns in thousands of neurons by combining two novel technologies: all-optical electrophysiology and BRAIN Initiative-funded fluorescent in situ hybridization, MERFISH. They will create correlated brain-wide maps of gene expression and neuronal firing, first in rodent acute brain slices and then in the zebrafish spinal cord in vivo . These maps may ultimately help elucidate the roles of genes in governing neural function in health and disease.

Novel neuromodulation, recording, and imaging techniques applied to human and non- human primate brains generate datasets that require tools for organizing, processing and analyzing data that are widely available and easy to use. Drs. Milham and Craddock plan to extend C-PAC (Configurable Pipeline for the Analysis of Connectomes), building a configurable data analysis pipeline that incorporates various statistical analysis, machine learning, and network analytic techniques. In addition to adapting methods used in human imaging for non-human primate data, the project will implement a toolbox for alignment of electrophysiological data with brain imaging data. The resulting software enables high- throughput, semiautomated and end-to-end processing and analysis of structural and functional MRI data that are accessed locally or via the cloud.

Systematic studies on the brain-spinal cord connectome are lacking despite great efforts to characterize neuronal cell types in the brain. Zhang’s multi- laboratories project aims to systematically characterize neuronal types in the mouse spinal cord based on their anatomy, connectivity, neuronal morphologies, molecular identities, and electrophysiological properties. Via multiple newly-developed techniques, including an anterograde/retrograde trans-synaptic tagging method to label neurons, gene expression bard coding, and a fast 3D light sheet microscopy method, the team will establish a complete cell-type based brain-spinal cord connectome database, which will be made accessible to the neuroscience community.

Recent tissue-clearing techniques and advances in microscopy have made it possible to produce 3D images of intact brains. to help ensure consistency in data collection and analysis, Dr. Hamilton and her team will develop a set of standards for3D imaging of whole brains for the neuroscience research community.. Dr. Hamilton’s group will convene a Working Group of experts who will work through a consensus process to establish standards that will be distributed to the research community. These standards should help improve the efficiency of imaging research and allow comparisons across studies.

Neuropharmaceuticals provide relief to millions suffering from an array of neurological and neuropsychiatric disorders. However, a barrier to identifying novel therapeutic targets can be attributed to a poor understanding of how the behavioral effects of drugs are mediated by specific neural cell types in the brain. Tadross’ team recently developed DART (Drugs Acutely Restricted by Tethering), the first and only method to date that can map the behavioral effects of clinical drugs by cell type. These tools would reveal circuit origins of desired vs harmful drug effects, explain why some drugs have higher efficacy than others, and potentially empower future rational efficacy advances. This project aims to expand the catalog of available DARTs, increase their subcellular specificity, and improve ease of use – particularly in combination with recording devices across larger brain areas. If successful, these tools will maximize utility to the neuroscience community, enabling previously intractable questions to be addressed.

This project develops DABI (Data Archive for the Brain Initiative) to aid the dissemination of human neurophysiological data generated through the BRAIN Initiative. Incorporating infrastructure from a pre- existing hub for delivering effective informatics and analytics solutions for major projects in the study of neurological diseases, Drs. Toga, Duncan, and Pouratian will aggregate data related to human electrophysiology, making the data broadly available and accessible to the research community. The group plans to incorporate analysis tools with user interfaces, implement tools for data management and use, and link metadata across different data modalities. The overarching goal of this project is to secure, link, and disseminate BRAIN Initiative data with all pertinent recording and imaging parameters coming from participating sites

Many labs develop unique software to manage and interpret their findings, but those programs are often specific for certain types of datasets, making them difficult to share among researchers. Dr. Van Hooser’s team plans to create an interface standard that establishes a common set of processes for accessing neurophysiological and imaging data. The standard will be tested, and revised accordingly, based on feedback from graduate students and postdoctoral researchers during data access events, or “hack-a-thons.” The interface standard will help increase the speed of research and make data widely available, allowing individuals outside of the neuroscience and research communities to make discoveries.

The precise number of neuronal cell types of about one hundred million highly-interconnected neurons in the mouse brain is unknown. Ultimately, the classification of neuronal cell types in the mammalian brain will require integrating molecular, morphological, and connectomic properties. Yang and colleagues propose to classify neuronal cell types via brain-wide comprehensive profiling of the dendritic morphology of neurons with subsequent digital reconstruction. Their transgenic mouse lines, MORF, enable sparse labeling of genetically-defined neurons in mice, which allow for the resolution and reconstruction of individual cells’ dendritic morphologies within densely populated neuronal networks. This project will help contribute to the BICCN effort to generate a reference mouse brain cell atlas, and data will be shared publicly through the BRAIN Cell Data Center.

To advance our understanding of the function of dynamical neural circuits, there is a need for technologies that can record the activity of hundreds to thousands of neurons simultaneously within and across brain regions in intact brains. Through Neural Dynamics Technologies, LLC, Drs. van Welie, Scholvin, and Boyden propose one way to resolve this issue by developing customizable high-density neural probes for use in acute or chronic recordings of neural population activity with a spatial and temporal resolution that is required for studying neural circuit activity.

Dr. Hobert and colleagues will create a highly selective technology for experimentally manipulating genes in neurons, by tapping into the regulatory machinery of individual cell types.

Low-cost, portable Magnetic Resonance Imaging (MRI) systems require use of small-bore magnets that are unable to capture the detail necessary to image the human brain. In this project, Drs. Wang and Wagner propose to further develop an imaging method previously funded by The BRAIN Initiative, by designing, building, and testing a portable 1.5T MRI system to image human brain activity. The novel imaging technology works with a small, lightweight (250 lb.), portable, low-cost, head-only magnet. The compactness and efficiency of this non-invasive imaging system makes the study of the human brain possible in more clinics and in subjects who previously were unable to receive an MRI scan due to constraints of standard systems.

Dr. Zhao's project aims to build a highly innovative and low-cost imaging tool that addresses a technological gap in neuroscience research for non-invasive recording of large neuron populations with high spatial and temporal resolution. The team plan to build and validate a fluorescent imaging system that enables parallel recording of multiple neuron populations with sub-cellular and sub-millisecond resolution. The system will include optimization of a benchtop microscope with two detection channels, and subsequent development of a head-mounted device for imaging in rodents. Successful development and commercialization of this technology could significantly advance neuroscience research, and thus improve our understanding of brain function.

Noninvasive neuromodulation technologies use a variety of electrical, magnetic, optical, and sonic techniques to stimulate the brain. The ensuing modulation of brain network dynamics can be used as a tool to study healthy brain processes, as well as for treatment of brain disorders. He’s team will develop an acousto-modulated electrophysiological source imaging (ESI) technique with improved spatial precision, and use it to monitor and image transcranial focused ultrasound (tFUS)-induced brain activity in real-time. The group will validate this integrated ESI-guided tFUS system in rats, using simultaneous intracranial recordings of neural spikes and local field potentials, and ultimately test it in human subjects. This non-invasive neuromodulation, with high spatiotemporal precision, promises stimulation which is individualized and responsive to dynamic neural activity.

Dr. Adey’s team will use advanced single cell analysis techniques to explore the epigenetic properties of non-neuronal brain cells. Techniques will include performing chromatin access assays and genome-wide profiling of DNA methylation, along with studying how a cell’s chromatin folds. Some of their methods will be used to profile and compare glial and vascular cells across brain regions in both rodents and humans. To help further understand the role of non-neuronal cells in the brain, the group plans to make these tools and data available to the research community for additional analyses.

Agency, our ability to act and experience a sense of responsibility for our actions, is central to individual identity and societal conceptions of moral responsibility. Neural devices are currently used to treat some brain disorders, such as Parkinson’s disease, and are being developed to treat others such as depression and obsessive-compulsive disorder, yet their use raises important ethical concerns about potential effects on agency. Dr. Goering, Dr. Klein and their team will investigate agency in individuals receiving brain computer interface devices for sensory, motor, communication, and psychiatric indications. They aim to build a user-centered neural agency framework, and, ultimately, to enhance the informed consent process by developing a communication tool that patient participants might use to better understand and discuss potential changes in agency associated with use of neural devices.

Molecular and cellular neuroscientists often lack the training in computer programming to fully explore “-omics” data common in the BRAIN Initiative. Drs. Hertzano and White will implement analytic software for visualization and interactive genome browsing of gene expression and RNA-seq data, including simple and complex cross-dataset analysis. These tools will be made available in the BRAIN Initiative funded Neuroscience Multi-Omic Data Archive (NeMO) which hosts multi-omic data. The software will provide an easy-to-use web-based work environment for visualization and analysis of multi-modality and multi- omic data, interrogation of relationships between epigenomic signatures and gene expression, and integration of analytical techniques for multivariate analysis, gene co- expression and other analyses.

Three-dimensional human brain atlases are increasingly important for integrating complex datasets into useful community resources. Fischl’s team proposes to create a multi-scale atlas—akin to Google Earth™ for the human brain—to map hemisphere-wide networks and also zoom in to see individual, labeled cells at micron resolution. This advance will be made possible through multiple imaging technologies, including light-sheet microscopy, tissue clearing, immunohistochemistry, magnetic resonance imaging, and newly-developed techniques in Optical Coherence Tomography. The ability to probe the cellular properties and multi-scale networks of specific areas in the human brain could evolve to an automated system for visualizing across the entire human brain in health and disease.

More than 500,000 children in the US and Canada suffer from epilepsy and 30% of these children continue to experience seizures despite being treated with anti-seizure medication. Unmanaged, epilepsy can result in cognitive decline, social isolation, and poor quality of life, and has substantial economic impact on families and society. Novel approaches for treating epilepsy such as vagal nerve stimulation and responsive neurostimulation are being developed, but this work has been conducted predominately in adults and the outcomes of these trials are often not clearly generalizable to children. In this project, Drs. Illes and McDonald will explore ethical issues confronting families and clinicians when considering new treatment options for drug-resistant epilepsy in children. They aim to develop, evaluate, and deliver patient-directed resources in the form of infographics and informational materials and videos, and clinician resources for family decision-making, clinician counseling, and care.

Brain-computer interfaces and neuroprosthetics have provided a significant benefit to patients with cervical spinal cord injuries. However, current technology is limited in its abilities to allow the user to control how much force is exerted by the prosthesis and to provide sensory feedback from the prosthetic hand. In a public-private collaboration with Blackrock Microsystems, Dr. Boninger and colleagues are looking to improve the dexterity of neuroprostheses by incorporating microstimulation of the somatosensory cortex. This stimulation could provide tactile feedback to the user and hopefully allow the user to better control the force applied. Ultimately, this approach will improve the dexterity and control of prosthetic limbs used by patients with spinal cord injuries.

The NIH BRAIN Initiative aims to catalyze novel tools and technologies to modulate brain circuit function, paving the way for new treatment options for brain disorders. However, such interventions also have the potential to cause unintended changes in aspects of cognition, behavior, and emotion. These changes, in turn, raise concerns regarding autonomy, personal identity, and capacity for informed consent. In this study, Dr. Cabrera Trujillo and her team will study ethical concerns, beliefs, and attitudes about the use of novel bioelectric approaches among clinicians, patients, and the broader public. The work will provide stakeholder perspectives that will be valuable for informing the responsible development and use of these novel neurotechnologies.

A camera that could image neuronal current distributions with a large array of pixels and a spatial resolution better than 1 ms resolution could dramatically enhance our understanding of neuronal circuitry. In this Phase I STTR, Fieldline, Inc. will develop a novel type of magnetographic camera, capable of providing single-shot images of electrical currents in neuronal circuits in vitro and in vivo with a millisecond time resolution. The team will first build a bench-top camera before combining it with electrode arrays, testing the ability to image neuronal connections across the circuit in vitro with turtle cerebellem. This will potentially lead to a completely portable, economical multi-pixel camera that can be produced for neuroscience research. 

Given the increasing use of magnetic resonance imaging (MRI) in brain research, understanding of what MRI signals really represent has become a fundamental yet fully elusive research topic. Recent neuroscience/neuroimaging research has also emphasized the importance of using multi-modal approaches, in which the data are acquired by multiple techniques to combine higher temporal resolution with spatial resolution of brain activity.  Drs. Shih and Franklin aim to bridge two of the most powerful and widely used research/clinical tools used in neuroscience – MRI and electrophysiology – by creating a novel MR-compatible 16-channel microelectrode array. This microelectrode array addresses two major applications: high resolution electrophysiology and deep brain stimulation. Both of which, in combination with simultaneous MRI, comprise a highly innovative platform which is intended to improve our understanding of brain function and neural circuit connectivity.

Given the increasing use of magnetic resonance imaging (MRI) in brain research, understanding of what MRI signals really represent has become a fundamental yet fully elusive research topic. Recent neuroscience/neuroimaging research has also emphasized the importance of using multi-modal approaches, in which the data are acquired by multiple techniques to combine higher temporal resolution with spatial resolution of brain activity.  Drs. Shih and Franklin aim to bridge two of the most powerful and widely used research/clinical tools used in neuroscience – MRI and electrophysiology – by creating a novel MR-compatible 16-channel microelectrode array. This microelectrode array addresses two major applications: high resolution electrophysiology and deep brain stimulation. Both of which, in combination with simultaneous MRI, comprise a highly innovative platform which is intended to improve our understanding of brain function and neural circuit connectivity.

A thorough understanding of brain function requires the integration of neuroscience data across species and scales. While current software can verify data quality within one or a handful of data sources, reproducibility across multiple data sources is limited. Xenophon Papademetris and colleagues are developing software tools with cross-scale, cross-species reproducibility analysis in mind. By leveraging data created by two other BRAIN Initiative projects at Yale University, Papademetris will extend current software algorithms to incorporate data from multiple sources, design the software to be cross-platform compatible, validate the software through rigorous testing, and finally, distribute it to the community. The potential for a set of software tools to reliably and reproducibly analyze multiple heterogeneous neuroscience data types will help to break down data barriers for the greater neuroscience community.

Three separate research groups are collaborating to understand in detail how three distinct areas of the brain function and work together to enable learning and decision-making behaviors. Drs. Kreitzer, Komiyama, and Lim are leveraging an impressive set of technologies to monitor and perturb different cell types in each brain region while the mice perform learning and decision-making tasks. By applying multiple recording methods across these brain regions at both the level of a single neuron and entire subpopulations of neurons, while the animals perform the same set of tasks, researchers hope to develop a single model of how vertebrate animals make choices about what to do next.

Penetrating electrode arrays have an expanding application in neuroscience research as they can provide direct access to neural signals across the central and peripheral nervous system with high spatial resolution. Chronic electrode implants could revolutionize treatment for a range of medical conditions, including prosthetic motor control and proprioception for amputees, and brain-machine interfacing for paraplegics. Unfortunately, device implantation applies forces to the neural tissue resulting in significant brain compression (dimpling) at the implant site, which increases risk of implantation trauma, bleeding and inflammation. Actuated Medical, Inc. will develop a neural implant inserter, the Ultrasonic Precision Insertion of Neural Devices (UPIND) system, that will reduce the insertion force by applying ultrasonic energy to electrode arrays during insertion. This system aims to enable greater placement control of floating microware arrays, while reducing tissue trauma.

Positron Emission Tomography (PET) has the potential to be an important tool in understanding the human brain. However, current PET systems used in oncology are expensive and lack the level of resolution necessary for human neuroimaging studies. Drs. Hunter and Coulis plan to combine a novel detector technology with innovative system architecture for commercial production of a cost-effective PET brain imaging system (Neuro-PET HD). In the Phase I STTR, PET/X LLC will create and validate the performance of a new PET detector ring system before generating a full commercial prototype. The goal is to reduce system cost, while providing a significantly more compact, mobile system that provides rigorously accurate images of brain function.

Star-shaped astrocytes are the most abundant non-neuronal cells of the brain. Their thin processes envelop neuronal synapses and critically shape their formation and function. In this project, BRAIN Initiative-funded researchers, Drs. Eroglu and Soderling, will develop and use a novel chemicogenetic approach called iBioID enabling the capture of astrocyte processes and the identification of the key proteins that form the interface between neurons and astrocytes. The team will use this technique in combination with gene editing to study how these proteins regulate the growth and maintenance of synapses in the healthy brain and explore what role they may play in neurological disorders.

When used in conjunction with transgenic animals to restrict expression to cell populations of interest, adeno-associated viruses (AAVs) can provide well-tolerated, targeted transgene expression enabling long-term behavioral, in vivo imaging, and physiological experiments. From previous BRAIN Initiative funding, Gradinaru’s team developed a method that allows systemic delivery of viral vectors capable of crossing the blood brain barrier, circumventing the need for transgenic animals. Here the team proposes to improve on this methodology by enabling select AAV variants to anterogradely cross synapses. This will be achieved through targeted evolution of AAVs. This ability to cross synapses with cell-specificity will also provide neural connectivity information. One could envision eventually being able to deliver therapeutics systemically that target disrupted circuitry with cell-specificity.

Neurophysiology research, which focuses on recording brain cell activity, produces enormous amounts of complex data that are difficult to manage. Drs. Rubel and Ng will build upon the Neurodata Without Borders: Neurophysiology project to create a system that will allow for standardizing, sharing, and reusing neurophysiological data. The team will design an open source software system; develop methods to establish a consistent vocabulary for defining cell types, measurements, and behavioral tasks; and create tools to help the community adopt these new resources and standards. The proposed system will help accelerate neurophysiological discoveries as well as reproducibility studies.

Magnetic Resonance Imaging (MRI) technology is being used to identify biomarkers in the central nervous system of children 6 months of age with Autism Spectrum Disorder (ASD). A potential promising group of biomarkers include data derived from both structural and functional MRI data acquired on infants. Dr. Bower’s group seeks to translate existing academic clinical research into a commercial product for potential clinical adoption by developing software that is a single, integrated, easy-to-use solution for MRI data collection, processing, and analysis for objectively evaluating a young child’s risk for ASD.

To leverage the public investment in the BRAIN Initiative, the sharing of data produced by its myriad projects is paramount. Dr. Podrack’s project extends the recently released OpenNeuro, which was developed based on the well-established and successful OpenfMRI, for an archive of neuroimaging data. The extended archive encompasses a broader range of neuroimaging data including EEG, MEG, diffusion MRI and others. The archive also implements easy-to-use data submission, semi-automated curation and advanced data processing workflows, which run directly on the cloud platform. The archive allows to share the results alongside the data, federate with other relevant repositories, and accessible to all researchers.

The brain consists of hundreds of molecularly, physiologically, and anatomically distinct cell types. Recently-developed methods can measure gene expression in tens of thousands of single cells, to help identify and classify many new types of brain cells. However, existing technologies capture only one aspect of gene regulation – mRNA levels. Dougherty’s team will develop a method to enable the parallel analysis of transcription factor binding and mRNA expression levels in mice to create single-cell Calling Cards, generating novel data and analysis tools. If successful, this project would contribute to neuroscience by providing a broadly useful technology for understanding brain function and development, in health and disease.

Though current implantable devices which can record neuronal activity in awake, behaving animals exist, Goodell and colleagues seek to increase the size and number of brain circuits that can be both measured and manipulated long-term. The group plans to engineer and implement a system that can control hundreds of implanted electrodes to record activity from cells at any location in the brain of non-human primates, and will couple this advancement with optogenetic technologies to control neuronal firing as well. These experiments, when applied to behaviors like visual discrimination, would dramatically enhance the ability of researchers to systematically map and characterize cortical function.

Electrocorticography (ECOG) allows the direct recording of a small population of neurons in human subjects, generating vast amounts of data. Dr. Beauchamp plans to develop the software RAVE (R Analysis and Visualization of Electrocorticography data) to help researchers explore such datasets. Incorporating established and successful informatics approaches that enable standardization, sharing, and re-use of neurophysiology data and analyses, RAVE includes rigorous statistical methodologies and seamless integration with existing analysis platforms. To facilitate user adoption and maximize impact, the developers plan to release RAVE 1.0 to the entire ECOG community within 6 months of the project start.

Studying how the brain works from the molecular to the circuit level is crucial for improving our understanding of how the brain functions normally, and what goes wrong in various disorders. Antibody probe techniques are effective tools that work at both of those levels. This project will develop a collection of validated, recombinant antibodies that are also highly renewable. In addition, antibodies will be miniaturized to increase binding efficiency and improve labeling precision. These resources will provide a cutting-edge, validated set of research tools to enable neuroscience research across a variety of resolutions from the intracellular to the neuronal network level.

Two-photon microscopy has emerged as a key technique for studying the activity of living neural networks. However, little optimization has been performed for the associated fluorescent activity probes and sensors. Dr. Drobizhev’s research group will create a resource at Montana State University to characterize the properties of two-photon probes and make that service available to the broader research community. Given increased used of this type of resource by BRAIN Initiative investigators, the research group will also organize meetings to help other labs develop their own characterization processes.

Neuroimaging techniques are advancing at a rapid rate, resulting in high resolution images of brain tissue and large datasets that can be difficult to manage. William Gray Roncal’s team propose an integration framework called SABER: Scalable Analytics for Brain Exploration Research. With a focus on techniques (e.g., electron microscopy) that produce high resolution brain images, SABER will create a unified framework by which these data types are accessible to a broader audience, can be processed in a reproducible, portable way, and can be scaled from small data volumes to large datasets. SABER has the potential to enable discoveries from high-resolution imaging techniques, making the parsing of entire brains a new reality.

Studying neural circuitry and function is particularly challenging in the human brain due to ethical considerations and the overall inherent experimental intractability of postmortem tissue. Furthermore, many aspects of human neurobiology are not fully recapitulated in small animal models, and research in large mammals is hindered by cost and experimental difficulties. Sestan’s team will optimize and validate a first-in-class neurotechnology, BrainEx, for the restoration of molecular and cellular functions of the postmortem large mammalian brain to allow connectivity and circuit tracing in myriad regions, as well as functional imaging. They aim to achieve this in the porcine model, in which brain size, complexity, and physiology are highly similar to human brains. These studies could establish the groundwork for the potential translation of this technology for conducting studies in the postmortem human brain.

Organoids, grown in laboratory settings to resemble parts of the developing human brain, hold great potential for shedding light on human brain function and disease. Researchers are working to achieve key bioengineering advancements, including successful vascularization of brain organoids, generating the full complement of cell types present in a human brain, and recording and modulating neural activity in organoids. These anticipated advances in bioengineered human brain modeling research may raise ethical questions about the moral status of large, complex human brain organoids and ethical boundaries on manipulating increasingly realistic engineered brain models. In this project, Dr. Hyun will lead proactive ethical discussions among ethicists and the neuroscientists conducting this cutting-edge work to develop greater awareness and understanding of these ethical implications and to inform future management of ethical issues that may be unique to this novel area of brain research.

Defining a complete cell atlas of the human brain, including a full molecular catalog of all its cell types and their spatial distribution, is a critical step toward understanding the human cognitive machine. Zhang’s team will expand on their previous efforts toward building a complete cell atlas of the whole human adult brain. They will systematically apply novel technologies for scalable, single-nucleus transcriptome sequencing, single-cell DNA accessibility assay, and in situ RNA imaging to MRI-scanned human brains, incorporating innovative computational approaches. If successful, the derived data will facilitate the study of molecular mechanisms underlying brain function and disorders, empowering the scientific community with a massive, readily accessible database of unprecedented scope.

Dr. Chung’s team aims to build a three-dimensional proteomic atlas of cells and neural circuits of human brains. To do this, his team plans to develop indestructible and transparent hydrogel-tissue hybrids for multi-rounds of protein labeling and imaging at subcellular resolution. They will stain the tissue via a variety of cellular and molecular labeling techniques and then use automated imaging to visualize different brain cell types, nerve fibers and synapses. The team will also create a supercomputing cloud- based framework and algorithms to analyze petabytes of high-resolution image data. This three- dimensional human brain atlas could give researchers a rapid, low cost way to discover brain cell types and the circuit problems behind neurological and neuropsychiatric disorders.