The BRAIN Initiative: Building, Strengthening, and Sustaining.

Successful federal initiatives share a focus on tangible success stories, constant input and guidance from scientists, participation by a wide range of funders, ongoing interest from policy makers, and a broad and effective communications network. By comparing these elements of the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative with other initiatives, we look at what needs to be done to sustain the BRAIN Initiative in the years to come.

High-Performance Computing in Neuroscience for Data-Driven Discovery, Integration, and Dissemination.

Opportunities offered by new neuro-technologies are threatened by lack of coherent plans to analyze, manage, and understand the data. High-performance computing will allow exploratory analysis of massive datasets stored in standardized formats, hosted in open repositories, and integrated with simulations.

Tools for the Microbiome: Nano and Beyond.

The microbiome presents great opportunities for understanding and improving the world around us and elucidating the interactions that compose it. The microbiome also poses tremendous challenges for mapping and manipulating the entangled networks of interactions among myriad diverse organisms. Here, we describe the opportunities, technical needs, and potential approaches to address these challenges, based on recent and upcoming advances in measurement and control at the nanoscale and beyond. These technical needs will provide the basis for advancing the largely descriptive studies of the microbiome to the theoretical and mechanistic understandings that will underpin the discipline of microbiome engineering. We anticipate that the new tools and methods developed will also be more broadly useful in environmental monitoring, medicine, forensics, and other areas.

Neurodata Without Borders: Creating a Common Data Format for Neurophysiology.

The Neurodata Without Borders (NWB) initiative promotes data standardization in neuroscience to increase research reproducibility and opportunities. In the first NWB pilot project, neurophysiologists and software developers produced a common data format for recordings and metadata of cellular electrophysiology and optical imaging experiments. The format specification, application programming interfaces, and sample datasets have been released.

A National Network of Neurotechnology Centers for the BRAIN Initiative.

We propose the creation of a national network of neurotechnology centers to enhance and accelerate the BRAIN Initiative and optimally leverage the effort and creativity of individual laboratories involved in it. As "brain observatories," these centers could provide the critical interdisciplinary environment both for realizing ambitious and complex technologies and for providing individual investigators with access to them.

Using Big Data to Understand the Human Condition: The Kavli HUMAN Project.

Until now, most large-scale studies of humans have either focused on very specific domains of inquiry or have relied on between-subjects approaches. While these previous studies have been invaluable for revealing important biological factors in cardiac health or social factors in retirement choices, no single repository contains anything like a complete record of the health, education, genetics, environmental, and lifestyle profiles of a large group of individuals at the within-subject level. This seems critical today because emerging evidence about the dynamic interplay between biology, behavior, and the environment point to a pressing need for just the kind of large-scale, long-term synoptic dataset that does not yet exist at the within-subject level. At the same time that the need for such a dataset is becoming clear, there is also growing evidence that just such a synoptic dataset may now be obtainable-at least at moderate scale-using contemporary big data approaches. To this end, we introduce the Kavli HUMAN Project (KHP), an effort to aggregate data from 2,500 New York City households in all five boroughs (roughly 10,000 individuals) whose biology and behavior will be measured using an unprecedented array of modalities over 20 years. It will also richly measure environmental conditions and events that KHP members experience using a geographic information system database of unparalleled scale, currently under construction in New York. In this manner, KHP will offer both synoptic and granular views of how human health and behavior coevolve over the life cycle and why they evolve differently for different people. In turn, we argue that this will allow for new discovery-based scientific approaches, rooted in big data analytics, to improving the health and quality of human life, particularly in urban contexts.

Straight talk with...Miyoung Chun. Interview by Virginia Hughes.

It was a single tweet. In February, after US President Barack Obama made a subtle nod to a new neuroscience project in his annual State of the Union address, Francis Collins, director of the country's National Institutes of Health (NIH), posted on the @NIHDirector Twitter feed: "Obama mentions the #NIH Brain Activity Map in #SOTU." Instantly, scientists were buzzing with rumors that the Brain Activity Map could be the next moon shot, with a budget and timeline similar to the Human Genome Project. The brain map began as a brief white paper and has grown into a large--and still largely undefined--collaboration of several government agencies, nonprofit foundations and private companies. As the stakeholders describe in a commentary published last month (339, 1284-1285, 2013), the goal of the initiative is to understand how thousands of neurons work in concert to control behavior and trigger disease. Miyoung Chun, vice president for science programs at The Kavli Foundation in Oxnard, California, has been developing the project since the beginning and is the self-described "glue" between its many diverse stakeholders. Chun spoke with Virginia Hughes about the evolution of the project and what it might mean for biomedicine.

Nanotools for neuroscience and brain activity mapping.

Neuroscience is at a crossroads. Great effort is being invested into deciphering specific neural interactions and circuits. At the same time, there exist few general theories or principles that explain brain function. We attribute this disparity, in part, to limitations in current methodologies. Traditional neurophysiological approaches record the activities of one neuron or a few neurons at a time. Neurochemical approaches focus on single neurotransmitters. Yet, there is an increasing realization that neural circuits operate at emergent levels, where the interactions between hundreds or thousands of neurons, utilizing multiple chemical transmitters, generate functional states. Brains function at the nanoscale, so tools to study brains must ultimately operate at this scale, as well. Nanoscience and nanotechnology are poised to provide a rich toolkit of novel methods to explore brain function by enabling simultaneous measurement and manipulation of activity of thousands or even millions of neurons. We and others refer to this goal as the Brain Activity Mapping Project. In this Nano Focus, we discuss how recent developments in nanoscale analysis tools and in the design and synthesis of nanomaterials have generated optical, electrical, and chemical methods that can readily be adapted for use in neuroscience. These approaches represent exciting areas of technical development and research. Moreover, unique opportunities exist for nanoscientists, nanotechnologists, and other physical scientists and engineers to contribute to tackling the challenging problems involved in understanding the fundamentals of brain function.

The brain activity map project and the challenge of functional connectomics.

The function of neural circuits is an emergent property that arises from the coordinated activity of large numbers of neurons. To capture this, we propose launching a large-scale, international public effort, the Brain Activity Map Project, aimed at reconstructing the full record of neural activity across complete neural circuits. This technological challenge could prove to be an invaluable step toward understanding fundamental and pathological brain processes.

Use of molecular imaging to quantify response to IKK-2 inhibitor treatment in murine arthritis.

OBJECTIVE: The NF-kappaB signaling pathway promotes the immune response in rheumatoid arthritis (RA) and in rodent models of RA. NF-kappaB activity is regulated by the IKK-2 kinase during inflammatory responses. To elucidate how IKK-2 inhibition suppresses disease development, we used a combination of in vivo imaging, transcription profiling, and histopathology technologies to study mice with antibody-induced arthritis. METHODS: ML120B, a potent, small molecule inhibitor of IKK-2, was administered to arthritic animals, and disease activity was monitored. NF-kappaB activity in diseased joints was quantified by in vivo imaging. Quantitative reverse transcriptase-polymerase chain reaction was used to evaluate gene expression in joints. Protease-activated near-infrared fluorescence (NIRF) in vivo imaging was applied to assess the amounts of active proteases in the joints. RESULTS: Oral administration of ML120B suppressed both clinical and histopathologic manifestations of disease. In vivo imaging demonstrated that NF-kappaB activity in inflamed arthritic paws was inhibited by ML120B, resulting in significant suppression of multiple genes in the NF-kappaB pathway, i.e., KC, epithelial neutrophil-activating peptide 78, JE, intercellular adhesion molecule 1, CD3, CD68, tumor necrosis factor alpha, interleukin-1beta, interleukin-6, inducible nitric oxide synthase, cyclooxygenase 2, matrix metalloproteinase 3, cathepsin B, and cathepsin K. NIRF in vivo imaging demonstrated that ML120B treatment dramatically reduced the amount of active proteases in the joints. CONCLUSION: Our data demonstrate that IKK-2 inhibition in the murine model of antibody-induced arthritis suppresses both inflammation and joint destruction. In addition, this study highlights how gene expression profiling can facilitate the identification of surrogate biomarkers of disease activity and treatment response in an experimental model of arthritis.