the future of neuroimaging: a 3d exploration of tbi
TRANSCRIPT
The Future of Neuroimaging: A 3D Explora9on of TBI
Hunter Whitney Jeffrey Chang, MD
Speakers
Hunter Whitney • UX Designer and Author of “Data Insights”
Jeffrey Chang, MD • ER Radiologist
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Disclosure
We have no financial or commercial conflicts of interest to disclose
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Agenda • Introduc9on / WIIFM • TBI Overview • UX Design Concepts • NEAAL Video • Improving on It – Imaging and User Control • Applica9ons in Research • From Research to Treatment • Brain Mapping – Current, Future and Complica9ons • The Purpose of a PlaXorm • Hunt for Ar9ficial General Intelligence
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The (Real) Final Fron9er: The Human Brain
Introduc9on
Blast medicine anyway! We've learned to 9e into every organ in the human body but one. The brain! The brain is what life is all about. -‐Dr. Leonard H. McCoy ("Bones") (from Star Trek TV series, The Menagerie)
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• Average weight of a human brain: 3 pounds • Number of neurons in the brain: 100 Billion • Miles of blood vessels, capillaries and other transport
systems in the brain: 100,000 miles • Number of connec9ons in the adult brain: 1 quadrillion
Gecng Inside Your Head is a Challenge
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“Since the brain is unlike any other structure in the known universe, it seems reasonable to expect that our understanding of its func9oning…will require approaches that are dras8cally different from the way we understand other physical systems.” -‐Richard M. Restak (from The Brain. The Last FronEer, 1979)
New Approaches
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Crea9ng useful new ways to model, visualize, and interact with many layers of data about the brain is vitally important for many purposes.
New Perspec9ves Needed
WIIFM – Investors’ Edi9on
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• This is the Brain Era – many of the next thirty years’ technological breakthroughs and their commercial applica9ons will happen right here
• New industry innova9ons revolu9onize our world each year – and they each relate to the future of thought, intui9on and analysis
• S&P 500 companies last 5 years on average – you must glimpse decades ahead in R&D
• SXSW 2013 – RIP Dell, Groupon, HP, B&N, RIAA
I’m a Dev – WIIFM?
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• Understand the issues
• Research in every field is remarkably varied
• Huge gulf between research and applica9on – the dev’s work can bridge that gap, through UI and by understanding each audience’s needs
• Investment pouring in, startups and funded brain mapping projects all need devs
Wait, Isn’t This the Research Track?
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• Connec9ng research done by many different groups – mul9ple disciplines working as one
• Breaking down silos within ins9tu9ons and across the world
• The beper you understand the target applica9on and end-‐goal, the more likely you’ll discover something truly revolu9onary – and the more likely you’ll get funding
• Have a say in the UI – what do you actually need?
Concept for Neuroimaging System
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We’re going to show an early concept for a neuroimaging system that could be used for many purposes, including research into trauma9c brain injury (TBI)
By examining the elements of something that is broken…
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…you can also gain more insight into how it normally works.
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TBI Overview
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Source: Robert T. Knight, M.D. Professor of Psychology and Neuroscience Department of Psychology Helen Wills Neuroscience Ins9tute
The impact of the problem…
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…con9nues to emerge.
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Many Complex Interac9ons
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Just as a car is made up of a range of different parts and materials that will be differen9ally impacted in a collision, far more so are the components of the brain. It is really only possible to figure out the full extent of damage retrospec9vely.
Mul9ple Factors
19 EMP (Electromagne8c Pulse)
Dynamic Forces
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UX Design Concepts
Gecng a Deeper Perspec9ve of Loca9on with 3D
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A 3D neuroimaging system that allows a fast, fluid inves9ga9on of heterogeneous data about the brain from the popula9on level down to a specific neural pathway in an individual pa9ent
Vision
NEAAL
(NeuroElectric and Anatomic Locator)
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High-‐level Goals for NEAAL
• Integra8on -‐ incorporate 3D anatomical visualiza9ons with related non-‐physical, data in a simple, elegant display
• Interac8on -‐ maximize visual display for primary work goals and employ verbal and gestural input for the func9onal tasks (NEAAL is no “WIMP”)
• Orienta8on -‐ help users maintain context as they move through an analy9c process while s9ll not overloading the display (ephemeral context)
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• Localiza8on -‐ allow users to quickly and easily hone in on and
mark points of interest
• Accelera8on -‐ enable faster workflows and more rapid, itera9ve hypothesis tes9ng.
High-‐level Goals for NEAAL (Cont.)
NEAAL Applies Ben Shneiderman’s Mantra
“Overview first, zoom and filter, then details-‐on-‐demand”
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Scenario for NEAAL
In 2008, a soldier in Afghanistan suffers a TBI…
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…and subsequent depression and PTE (post-‐trauma9c epilepsy).
Certain notable features of the case are flagged by the clinician and aggregated with similar cases History & Physical
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Certain PTE Cases with Characteris9c Apributes are Aggregated
History & Physical Aggregated H&P Data
Aggregated View
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A Researcher Starts with the Aggregate and then Moves to the Individual Case
Individual View
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Aggregate View
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Integra8on
Paths
Loca9on and Scale
Structural, Func9onal, Cogni9ve, Demographic
Views
Inves9ga9ve and Anatomical
The Big Picture
H&P CT
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CT
Popula9on
Cog
ANAM
H&P
PTE Inves8ga8on
Steps of an Inves9ga9on (PTE)
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CT
Popula9on
Cog
ANAM
Steps of an Inves9ga9on (Depression)
H&P
Depression Inves8ga8on
Traveling on an Anatomical Path with Different Imaging Modali9es
MRI + DTI
DTI
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Scale Changes from Large Structural Features to Discrete Neural Tracts
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Remember the Future?
Deckard’s Image Scanner
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“Enhance 15 to 23”
Image Scanner Next Gen
What can be improved?
• The Blade Runner vision is interes9ng but would be cumbersome for the researcher in our scenarios; mul9modal 3D is a more robust and easier to use vision.
• Another Image Scanner Next Gen idea…
“Print a hard copy.” Why not do that with a 3D print of the brain and locus of injury?
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NEAAL Video
Disclaimer: Imaging Limita9ons
42 San&ago Ramón y Cajal, Drawing of a single neuron, 1899 Jiang X et al. The organizaEon of two new corEcal interneuronal circuits, Nature Neuroscience 2013
MVP Concept Disclaimer
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• Consider a dynamic interface – Gestural control of the flyover – Rapid gestural or voice-‐driven zoom and manipula9on
– Instant localiza9on of any part of the brain – Tracks mul9ple modali9es at once, and remembers which overlays provide complementary informa9on
Imaging will change …
44 Improved Stroke Imaging Techniques, JAMA 1999
Zhang, W. et al. Landmark-‐referenced voxel-‐based analysis of diffusion tensor images of the brainstem white ma]er tracts. NeuroImage 2009
Laundre, B et al. Diffusion Tensor Imaging of the CorEcospinal Tract before and a^er Mass ResecEon. AJNR 2005
Christoforidis, G. et al. “Tumoral Pseudoblush” IdenEfied within Gliomas at High-‐SpaEal-‐ResoluEon Ultrahigh-‐Field-‐Strength Gradient-‐Echo MR Imaging. Radiology 2012
We will live to see the end of the
mouse …
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Non-‐Invasive BCI
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Emo8v EPOC -‐ 2008
g.Tec intendiX-‐ SPELLER -‐ 2012
EPOC with AutoNOMOS-‐Labs
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What Other Applica9ons Need Robust Tools?
One plaXorm, mul9ple possibili9es
• Tissue Bioengineering
• Organism Simula9on
Tissue Bioengineering?
48 From Mosby Year-‐Book
Anthony Atala: PrinEng a Human Kidney (TED 2011)
Organism Simula9on – for Aging, Disease and Pharma
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Modeling of a Biological Cell Model, MarEn Falk, Universität Stu]gart
Marcus Covert Systems Biology Lab, Stanford
From Research to Treatment
50 Dr. Balaji Anvekar’s Neuroradiology Cases; SP Ins9tute of Neurosciences, Solapur, India -‐ 2012
AI in the Hyperacute Response
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Keyhole neurosurgery – EU ROBOCAST • Bigger robot holding smaller robot
July 2011, Baghdad – Wealth of Health / Neuroscience News
The Future of TBI Treatment
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Studies of axonal regeneraEon in Drosophila (fruit flies), Melissa Rolls, Penn State University
Nerve Replacement Strategies for Cavernous Nerves May, F et al. European Urology 2005(48:3) Salvador, G. Uranga, R and Giusto, N. Iron and Mechanisms of Neurotoxicity.
InternaEonal Journal of Alzheimer’s Disease, 2011
Hurdles to Healing the Aging Mind
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Scheltens, Philip. Imaging in Alzheimer’s Disease. Dialogues in Clinical Neuroscience 2009(11)
• The road from Assis9ve Robo9cs to Automa9on
• Automated clinical care algorithms, especially with a new genera9on of physicians
• Rapid tes9ng, immediate results for more labs and radiology, shortened stays (ACO models)
Disrup9ng a Conserva9ve Industry
54 Automated ICU SedaEon @ Georgia Tech – Wassim Haddad, Allen Tannenbaum and Behnood Gholami
Prof. Allison Okamura’s HapEc ExploraEon Lab at JHU (now at Stanford)
Brain Mapping IBM Researchers Create the Most Detailed Brain Map Yet “A significant stride towards reverse-‐engineering the darn
thing.”
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July 27th, 2010 410 papers, 50 years, CoCoMac database of the Macaque brain 383 brain regions, 6,602 directed long-‐distance connec9ons
“The data is of the monkey, by the people, and for the people.” – Dharmendra Modha, SyNAPSE
CLARITY – innova9on beckons
56 CLARITY – Intact mouse brain stained with fluorescent protein-‐specific labels. Kwanghun Chung and Karl Deisseroth, Howard Hughes Medical Ins8tute / Stanford University
The Growing Wave
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“The Next Fron9er”
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I think the biggest innova&ons of the 21st century will be at the intersec&on of biology and technology. A new era is beginning.” – Steve Jobs, 2011
Building the Universal PlaXorm
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Rita Carter – Mapping the Mind: Revised and Updated EdiEon (2010)
Milky Way will collide with Andromeda in 4 billion years; courtesy of NASA
Problem #1
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Problem #2
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Problem #3
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It’s Even More Complicated
Sprout Labs Australia Buxhoeveden, D. and Casanova, M. The minicolumn hypothesis in neuroscience. Oxford Journals: Brain 2001
Issues with the Mind
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Men ought to know that from the brain, and from the brain only, arise our pleasures, joy, laughter and jests, as well as our sorrows, pains, griefs, and tears.
– Hippocrates of Cos (circa 400 BC)
What Counts as a Mapped Brain?
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The PlaXorm as a Guide
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Progress in Brain Mapping
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Allen Ins8tute for Brain Science (2003)
$300M from 2012-‐2016
Human Brain Atlas – 2011
Progress in Brain Mapping
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The Human Connectome Project Started August 2012, $30M UCLA – MGH, Washington U. – U. Minnesota
LPBA – the ProbabilisEc Brain Atlas at UCLA
Progress in Brain Mapping
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Aggrega9on of 1200 brain MRIs, including 300 pairs of twins Increasing resolu9on of the reference MRI map to 1 mm
MarEnos Center at MGH (Harvard)
The Future of Brain Simula9on
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“CERN For The Brain” The Human Brain Project @ EPFL (Lausanne, Switzerland) Awarded €1.19B over 10 years by the EC’s FET flagship Compila9on of global neuroscience data, will build plaXorm to help researchers with neuromorphic compu9ng and designing neurorobo9cs Collabora9ve effort Blue Brain + 87 European and interna9onal partners
10,000 simulated neurons, 30 million synapses, forming part of a single corEcal column in the rat brain; from HBP in 2008
The Supercomputer Approach
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TrueNorth, on LLNL’s Blue Gene / Q Sequoia (2nd fastest supercomputer in the world)
96 racks (1,572,864 cores, 1.5PB memory, 6,291,456 threads)
553.5 billion neurons
100 trillion synapses (DARPA’s SyNAPSE)
1 / 1542 the speed of the human brain
The actual human brain has 86 – 100 billion neurons and 100 trillion to 1 quadrillion synapses; average es9mate at 350 trillion synapses
Simula9on at approximately 4.8%, or 1/20th, the synap9c density of the human brain (synapses per neuron)
Each dot represents a neurosynapEc core, containing 256 neurons; 1024 synapses per neuron. 2.084 billion cores, divided into 77 brain regions, using the macaque brain as the template
Func9on-‐Focused
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Spaun – U. Waterloo Largest simula9on of a func9oning brain, with 2.5 million separately modeled spiking neurons Performs a variety of tasks; very useful as a model for managing the flow of informa9on through a large system,
Culturing the Brain
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To understand the development of synapses and spontaneous excita9on on a cellular level
MIRA InsEtute, University of Twente – November 2012; neurite morphology in a simulated Petri dish of 10,000 neurons
Living Neural Networks
74 Removing some ‘A’ from AI: Embodied Cultured Networks (2004) – GA Tech, MIT, U. Western Australia, U. Florida (follow-‐up global research from 2004 to 2012)
Simula9ng the Brain in Real Time
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Neurogrid
Modeling selec&ve aPen&on in the visual cortex, by increasing the gain of excitatory neurons. Analog computa9on (parallel) to emulate ion-‐channel ac9vity, and digital synap9c connec9ons. Simulates 1 million neurons and 6 billion synapses in real-‐9me, using only 5 waps of power
Nick Steinmetz, 2011 @ Stanford
AI – The Eternal Horizon
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The Road to AGI
77 Sandberg, Anders; Bostrom, Nick (2008). Whole Brain EmulaEon: A Roadmap. Future of Humanity InsEtute, Oxford University
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Lvl Extent of Whole Brain Emula8on
# of en88es Storage Demands (Tb)
Earliest Year ($B projects)
CPU Demand (FLOPS)
Earliest Year ($B projects)
2 Brain Region Connec8vity
105 regions, 107 connec9ons
3 x 10-‐5 Achieved -‐-‐ Achieved
3 Analog network popula8on model
108 popula9ons, 1013 connec9ons
50 Achieved 1015 Achieved
4 Spiking neural network
1011 neurons, 1015 connec9ons
8,000 2016 1018 2018
5 Electrophysiology 1015 compartments x 10 state variables
10,000 2016 1022 2030
6 Metabolome 1016 compartments x 102 metabolites
106 2024 1025 2040
7 Proteome 1016 compartments x 103 proteins
107 2028 1026 2044
8 State of protein complexes
1016 compartments x 103 proteins x 10 states
108 2031 1027 2047
9 Distribu8on of complexes
1016 compartments x 103 proteins x 100 states
109 2035 1030 2057
10 Stochas8c behavior of single molecules
1025 molecules 3.1 x 1014 2055 1043 2100
11 Quantum states Approx. 1026 atoms Using Qbits ? Using Qbits ? Sandberg, Anders; Bostrom, Nick (2008). Whole Brain EmulaEon: A Roadmap. Future of Humanity InsEtute, Oxford University
The AGI Timeline
79 Sandberg, Anders; Bostrom, Nick (2008). Whole Brain EmulaEon: A Roadmap. Future of Humanity InsEtute, Oxford University
The Singularity?
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“In the future, search engines should be as useful as HAL in the movie 2001: A Space Odyssey – but hopefully they won’t kill people.” – Sergey Brin
“In the game of life and evolu&on there are three players at the table: human beings, nature, and machines. I am firmly on the side of nature. But nature, I suspect, is on the side of the machines.” – George Dyson
AGI – Current Efforts
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Vicarious, Genifer, Numenta, OpenCog, OpenNARS, A2I2, Cyc, Soar, the Google Moonshot Factory
Every &me I talk about Google’s future with Larry Page, he argues that it will become an ar&ficial intelligence.” – Steve Jurvetson, Draper Fisher Jurvetson
The Next Decade 1. Building the necessary tools,
for discovery and applica8on
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If you invent a breakthrough in ar&ficial intelligence, so machines can learn, that is worth 10 Microso\s.” – Bill Gates, 2004
2. Keeping abreast of the 8meline for Brain Mapping efforts; finding the right ques8ons to ask, for new weak AI applica8ons
3. Will your startup’s logo be on this slide in 2023?
Acknowledgments
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Special Thanks: Michael Aratow, MD Lee Hall, M.D. Jason Collins, Canopy Partners Jeanne Rayne, Canopy Partners Veena Kumar, MD, MPH Paul Laurien9, MD The zSpace team
Video Produc8on: Spencer Lindsay, Lindsay Digital Ruby Rieke