How can we har­ness the Human Brain Project to max­i­mize its future health and well-being ben­e­fits?


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In early 2013, the Euro­pean Union selected the Human Brain Project, coor­di­nated by Lausanne’s Fed­eral Insti­tute of Tech­nol­ogy (EPFL), as the recip­i­ent of over 1 bil­lion euros/ 1.3 bil­lion dol­lars over the next ten years. How can the research agenda of this major ini­tia­tive, and closely related ones, be orga­nized and aug­mented with part­ner­ships with the pri­vate sec­tor and cross-sector stake­hold­ers? How can we start build­ing brain heath inno­va­tion plat­forms and deliv­ery sys­tems at the inter­sec­tion of neu­ro­science, IT, and engineering?
- Chair: Hilal Lashuel, Asso­ciate Pro­fes­sor at the Swiss Fed­eral Insti­tute of Technology-Lausanne (EPFL), YGL Class of 2012
- Sean Hill, co-Director of the Blue Brain Project and co-Director of Neu­roin­for­mat­ics in the Human Brain Project (HBP) at the Swiss Fed­eral Insti­tute of Technology-Lausanne (EPFL)

This session took place at the 2013 SharpBrains Virtual Summit:

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How can we har­ness the Human Brain Project to max­i­mize its future health and well-being ben­e­fits?

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  2. 2. Chaired by: Hilal Lashuel Associate Professor at the Swiss Federal Institute of Technology-Lausanne (EPFL), YGL Class of 2012 Sean Hill, co-Director of the Blue Brain Project and co- Director of Neuroinformatics in the Human Brain Project (HBP) at the Swiss Federal Institute of Technology-Lausanne (EPFL) How can we harness the Human Brain Project to maximize its future health and well-being benefits?
  3. 3. The Human Brain Project Co-Executive Directors: Henry Markram, Brain Mind Institute, EPFL, Switzerland Karlheinz Meier, Kirchoff Institute, University of Heidelberg, Germany Richard Frackowiak, Department of Clinical Neurosciences, CHUV, Switzerland Sean Hill Co-Director, Neuroinformatics, Human Brain Project Director, Neuroinformatics, Blue Brain Project EPFL, Lausanne, Switzerland
  4. 4. 4 Upon this gifted age, in its dark hour,Rains from the sky a meteoric showerOf facts . . . they lie unquestioned, uncombined.Wisdom enough to leech us of our illIs daily spun; but there exists no loomTo weave it into fabric; Edna St. Vincent Millay, 1939
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  6. 6. 6
  7. 7. 7 Developmental Disorders ’ Adolescent Disorders ’ Adult Disorders ’ ’ ’ Aging Disorders Glutamate Nutrition Dopamine Genes Sugar GABA Myelin Serotonin Metals Dopamine Toxins Acetylcholine Protein misfolding
  8. 8. 9 Microarrays Electron Microscopy Confocal Microscopy Single Cell PCR Protein quantification Magnetic bead Gene sequencing Gene silencing Gene over- expression Genetic vectors Two-hybrid system Protein separation Wholecell & Inside-Out Patch Laser micro- dissection Cell culture Fluorescence microscopy Cellular tracing Cell sorting In situ hybridization Rhodopsin vectors Immuno-detection amplified by T7 Mass- spectroscopy Organelle transfection Spatial Proteomics Immuno- staining Multi Electrode Array Extracellular Recording Dye Imaging 2DE proteomics Tissue transfection Enzymatic-activity measurement Behavioral Studies Ultramicroscopy Magnet Resonance Diffusion Imaging fMRI EEG Transgenic lines
  9. 9. What is the Human Brain Project? A 10-year European initiative to launch a global, collaborative effort to understand the human brain, enabling advances in neuroscience, medicine and future computing. One of the two final projects selected for funding as a FET Flagship from 2013. A consortium of 256 researchers from 146 institutions, in 24 countries across Europe, in the US, Japan and China.
  10. 10. 11 What is a FET Flagship? Future and Emerging Technologies (FET) Flagships are ambitious large-scale, science-driven, research initiatives that aim to achieve a visionary goal. The scientific advance should provide a strong and broad basis for future technological innovation and economic exploitation in a variety of areas, as well as novel benefits for society. Objective is to keep Europe competitive and drive
  11. 11. Goal The Human Brain Project should: •Lay the technical foundations for a new model of ICT-based brain research •Drive integration between data and knowledge from different disciplines •Catalyze a community effort to achieve a new understanding of the brain,
  12. 12. Research Areas Neuroscience Integrate everything we know about the brain into computer models and simulations Medicine Contribute to understanding, diagnosing and treating diseases of the brain Future Computing Learn from the brain to build the supercomputers of tomorrow
  13. 13. 14 Scientific organization
  14. 14. Data Generate and interpret strategically selected data needed to build multilevel atlases and unifying models of the brain.
  15. 15. 16 The Data Ladder to the Human Brain
  16. 16. Data However, HBP is NOT primarily a data generation project It IS a data integration project.
  17. 17. 18 Build, Simulate and Validate Unifying Brain Models
  18. 18. Six new ICT platforms: •Neuroinformatics •Brain Simulation •Medical Informatics •High Performance Computing •Neuromorphic Computing •Neurorobotics For the entire research community. ICT Platforms
  19. 19. 20 Neuroinformatics Platform Provide technical capabilities to federate neuroscience data, analyze structural and functional brain data and to build and navigate multi-level brain atlases. This involves: •spatial and temporal data registration •ontology development and semantic annotation •predictive neuroscience •machine learning, data mining •track provenance, build workflows. Goal: enable an integrated
  20. 20. 21 Data management strategy ’
  21. 21. 22 Knowledge integration strategy
  22. 22. 23 Multiscale and Multimodal Brain Atlases Atlases - collections of spatially and semantically registered and searchable data, models and literature Highly controlled data for building models Other data for validations
  23. 23. 24 Brain Simulation Platform Provide technical capabilities to build and simulate multi-scale brain models at different levels of detail. •internet portal for neuroscientists •modeling tools •workflows •simulation •virtual instruments (EM, LFP, fMRI, etc) •link to virtual body and environment •in silico experiments Goal: Integrate large volumes of heterogeneous data in multi- scale models of the mouse and human brains, and to simulate
  24. 24. 25 Ontology and Index Representation Mapping Region Geometry Volume Dendrogram 3D Points Volume Mesh Electrodynamics and Phenomenological Descriptions PhysicalChemistry FieldPhysicsandFluidDynamics Surface Mesh Particle Tracking Microcircuit Brain Simulation Platform: Multiscale representations
  25. 25. 26 Brain Simulation Platform: Multiscale solvers
  26. 26. 27 Integration of laboratory data 27 S1L1 Neocortical Microcircuit 30’000 neurons 400 Electrical Behaviors Gene profiles Synaptic profiles Morphology profiles Connectivity profiles Electrical profiles Circuit profiles Protein profiles
  27. 27. Automatically building neuron models g=gNa m3h Inactivating Na Channel Non Inactivating K Channel g= gk n4 Distribution •Staining, Literature, Assumed •Given Somatic Distance Function •Fitted within given tolerance Relative Density •Data constrained •Generic algorithm single cell rtPCR gene expression profile Ion Channels 1.Nap, Fast Na+ 2.Natt, Persistent Na+ •Kfast, Delayed Rectifier K+ •Kslow, Slow K+ •Kt, Transient K+ •LVA Ca2+ •HVA Ca2+ •Ih, H-Current •Im, M-Current •BK, Large g, Ca2+ activated K+ •SK, Small g, Ca2+ activated K+ •Leak Current Composition •Single cell RT-PCR •ISH expression distribution •literature ~400 compartments ~8000 segments ?
  28. 28. 29 Brain Simulation Platform Data-driven biophysical single cell models Hay et al., PLOS Comp. Biology, 2012
  29. 29. 3030 Predictive Neuroscience: One example Hill et al. PNAS 2012 2,970 possible synaptic pathways in a cortical microcircuit alone. 22 have been characterized. Can we identify principles to predict the rest?
  30. 30. 31 Brain Simulation Platform Cortical microcircuitry
  31. 31. 32 Brain Simulation Platform Cortical microcircuitry and local field potential Reimann et al., Neuron, 2013 in collaboration with the Allen Institute, Seattle, WA
  32. 32. 33 Simulated in vitro cortical slice preparations Brain Simulation Platform
  33. 33. 34 High Performance Computing Platform Provide the project and the community with: •The computing power necessary to build and simulate models of the brain. •Develop new supercomputing technology, up to the exascale •Drive new capabilities for interactive computing and visualization.
  34. 34. 35 Computational Complexity Memory Requirements O(1 MB) O(10 GB) O(1 TB) O(100 TB) O(100 PB) Single Cell Model Cellular Neocortical Column O(10,000x cell) Cellular Mesocircuit O(100x NCC) Cellular Rat Brain O(100x Mesocircuit) Cellular Human Brain O(1,000x Rat Brain) O(Gigaflops) O(10 Teraflops) O(100 Teraflops) O(1 Petaflops) O(1 Exaflops) EPFL 4-rack BlueGene/L CADMOS 4-rack BlueGene/P Reaction-Diffusion O(1,000x memory) Reaction-Diffusion O(1,000x memory) Reaction-Diffusion O(1,000x memory) Glia-Cell Integration O(10x memory) Vasculature O(1x memory) Particles O(10-100x memory) Reaction-Diffusion O(1,000x memory) Glia-Cell Integration O(10x memory) Vasculature O(1x memory) Reaction-Diffusion O(100-1,000x performance) Plasticity O(1-10x performance) Local Field Potentials (1x performance) Reaction-Diffusion O(100-1,000x performance) Glia-Cell Integration O(1-10x performance) Vasculature O(1x performance) Electric Field Interaction O(1-10x performance) Plasticity O(1-10x performance) Reaction-Diffusion O(100-1,000x performance) Glia-Cell Integration O(1-10x performance) EEG (1-10x performance) Vasculature O(1x performance) Plasticity O(1-10x performance) Behavior O(10-100x performance) Reaction-Diffusion O(100-1,000x performance) High Performance Computing Challenges
  35. 35. 36 Medical Informatics •Federate clinical data from hospital archives and proprietary databases, while providing strong protection for patient data. •Enable researchers to identify “biological signatures” of diseases. Develop new approaches to understanding the causes of disease and identifying effective treatments
  36. 36. 37 Disease signatures
  37. 37. 38 Neuromorphic Computing Platform Simulate models on low power chips. Build off of BrainScaleS and Spinnaker projects to provide ability to run large- scale simulations at or beyond real time with low power consumption.
  38. 38. 39 Neurorobotics Platform Virtual bodies, sensory input and environments to couple with the simulations. This platform is key to providing sensory input to the simulations and depicting the motor outputs.
  39. 39. 40 Applications: Understanding principles of cognition
  40. 40. Applications: Developing new drugs for brain disorders
  41. 41. Applications: Developing neuromorphic controllers
  42. 42. Theory Theory enables effective application of knowledge about the brain to medicine or computing.
  43. 43. Society and Ethics “A far-reaching Society and Ethics program, funding academic research into the potential social and economic impact of HBP research, and its ethical and conceptual implications… …managing programs to raise ethical and social awareness among HBP researchers, and, above all, encouraging an intense dialog with stakeholders and with civil society.”
  44. 44. 45 Participating Scientists
  45. 45. ~20% of funding (~200M€) allocated to open calls
  46. 46. 4848 For more information and a full list of leaders, partners and collaborators please visit: The Initial HBP Consortium
  47. 47. 49 Q&A 10 minutes (Included in session recording)
  48. 48. Sponsors Partners Thank You for Joining Us!
  49. 49. To Learn More… Summit Recordings Book Market Report sharpbrains. com/book/ sharpbrains. com/summit/ /market-report/