KAVLI NDI Research

OBJECTIVES

Kavli NDI is motivated by recent successes in genetics, cosmology, and particle physics. These fields have been able to answer fundamental questions within thier discipline by fostering transdisciplinary interactions, at a global scale, while also illuminating our understanding of our world. Our research model at Kavli NDI is to create a microcosm of such successful global systems and seed a worldwide effort to revolutionize neuroscientific research.

  • DATA ACQUISTION

    • To advance our understanding of the brain, experimental methodologies must increasingly capture biological structure and function at high resolution across a range of spatial and temporal dimensions. Now more than ever, a multi-dimensional approach is critical to allow for discovery in many areas of neuroscience, from genes and signal transduction networks to cellular connectomics and physiology to interactions between brain areas mediated by long-range neuronal projections in behaving organisms. Large-scale datasets (e.g., hundreds of terabytes) present challenges for database construction, analyses, and accessibility that will require the coordinated efforts of many research groups with diverse expertise ranging from genetics to engineering.

  • TECHNOLOGY DEVELOPMENT

    • Experimental neuroscientists face considerable obstacles to the rapid introduction of new technologies that are essential to advance understanding, as they often do not possess the knowledge necessary to design and construct novel instrumentation. Engineers often do not understand the particular challenges of working with biological systems, impeding innovation. This duality results in unnecessary hindrance in the process of developing the next generation of tools for studying the brain. Kavli NDI eliminates these barriers by bringing together neuroscientists, engineers and theorists early and often to accelerate discovery.

  • COMPUTATION AND ANALYSES

    • To understand the exceedingly complex, multi-scale networks of the brain, renewed efforts must be made to develop rigorous theoretical models based on our ever-expanding experimental knowledge base. Creative breakthroughs in understanding brain function require extensive collaborations between biologists, engineers and theorists. At Kavli NDI, theory and computational modeling play an essential role in designing, analyzing and interpreting biological experiments and in creating new theoretical frameworks for understanding brain function.

  • RESEARCH ORGANIZATION

    • To ensure success of our research objectives, Kavli NDI at Johns Hopkins is organized to span three Pillars of Innovation 

      I. NeuroEngineering: Building innovative tools to measure, manipulate, and model within and across spatiotemporal scales. 

      II. NeuroExperiments: Leveraging these tools to conduct cutting-edge experiments to monitor and manipulate brain circuits.

      III. NeuroData: Converting experimental data into discovery via computational solutions to analyze, interpret, and share large-scale neural datasets via statistical machine learning and cloud computing.

       

       

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