Supporting the complex requirements of a long-term project for whole brain emulation

648 views

Published on

There is a rationale from both social and personal perspectives that leads to the need for strong adaptability that can be solved by "uploading" to substrate-independent minds. I will briefly state that rationale and then look at the concrete problem of how mental functions can become substrate independent, especially through the process of whole brain emulation (WBE).
The central problem of the paper is how to address the many complex requirement on the roadmap to WBE, given that it is a long-term project and the trends in science and technology are strongly guided by actions with rapid pay-off. The possible futures may be quite different, depending on whether society follows trends that are heavier on machine-centric improvements or those where human and machine develop together. How can one ensure that the requirements of a complex long-term goal are met by the scientific and technological pursuits of a loosely coupled multi-disciplinary network?
I will then propose a method that is based on monitoring and nurturing from a big-picture perspective, selecting successive key focal points for attention. I give the recent example of missing tools for high-resolution large-scale activity recording in brain tissue, then highlight how targeted actions were involved in the emergence of solutions that are now lab prototypes.
Building on that example, I demonstrate 1.) the importance of goal-driven activity that is applied iteratively and 2.) the importance of follow-up activity to take the consequent developments to the level of "application platforms", so that trends may begin to point to whole brain emulation goals.
In conclusion, I will show that this process can lead to piece-wise and sustainable development of whole brain emulation where each step delivers applications and rewards (e.g. brain-machine interfaces, neural prostheses, neural enhancements).

Published in: Science
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
648
On SlideShare
0
From Embeds
0
Number of Embeds
42
Actions
Shares
0
Downloads
9
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

Supporting the complex requirements of a long-term project for whole brain emulation

  1. 1. Supporting the complex requirements of aSupporting the complex requirements of a long-term project for whole brain emulationlong-term project for whole brain emulation Dr. Randal A. KoeneDr. Randal A. Koene Carboncopies.orgCarboncopies.org MTA2014
  2. 2. OVERVIEW Brief Basics + Rationale for WBE Success of Long-Term Project with Complex Requirements Proposed Method & Example from Experience A Piece-Wise, Sustainable Path to WBE
  3. 3. BASICS: TERMINOLOGY http://koene.carboncopies.org Objective: SIM Substrate-Independent Mind Feasible method: WBE Whole Brain Emulation Bio to WBE transfer: “mind uploading”
  4. 4. BASICS: PURPOSE In Search of Everything Personal limitations To Understand Everything To Create Anything Enhance & Expand Capabilities: Need ACCESS Brain Interfaces & ultimately SIM give maximum access & maximum flexibility
  5. 5. BASICS: ADAPTABILITY FOR OUR SPECIES Suitable for this environment, this little niche in time and space Bigger picture perspective: Many challenges we are not at all suited for Changes are coming, we may even be causing them! Species Survival & Species Thriving require excellence in adaptability Responsibility to prepare our species while we can
  6. 6. BASICS: REVERSE ENGINEERING A MIND Small Brain Prostheses show it IS POSSIBLE: Cochlea, Retina & HIPPOCAMPUS Hippocampus: Episodic Memory Biomimetic chip replaces function Works in rats (many experiments), works in monkeys 3 years to human trials! Berger et al, USC
  7. 7. BASICS: SYSTEM IDENTIFICATION Unknown Sysem (bio / chip) = black box with I/O Know your goal, discover relevant signals (chip example: 1s & 0s) Berger hippocampus: assume “spike” times are relevant: evidence in sensory, motor & synaptic change Learn transfer function for input spike patterns to output spike patterns NOT the same as a 'simulation' that abstracts function
  8. 8. BASICS: WBE IS MANY CONNECTED PROSTHESES Whole Brain roadmap: Break black box with 100B neurons into many connected sub-systems as feasible or smaller than Berger's Connections tell us how sub-systems can interact Characterize function within each sub-system Emulate dynamic function representations Test & Iteratively improve Structure: Connectome Proof-of-concept 2012 Function: each neuron? Current Aim! Emulation: model platform Application & Validation
  9. 9. MISSION: LONG TERM & MANY REQUIREMENTS Tech. requirements to iterate towards on 4 pillars Actual R&D activitiy based on short-term interests Trends may not lead to goals without a special effort What may happen if other trends dominate, e.g. AI?
  10. 10. MISSION: CARBONCOPIES.ORG Maintain a roadmap: Know goals in terms of requirements + actual activity / trends Top-Down needs Bottom-Up feasibility Encourage meeting requirements and filling gaps by emphasizing / starting specific activities Big-picture vigilance: apply where most needed
  11. 11. METHOD: EXAMPLE, 2013 FOCUS High-resolution functional data acquisition 'every neuron' Boyden (MIT) to Silicon Valley 2012: Molecular Ticker Tape & Brain Activity Map (BAM) Carmena (UC Berkley) interest in WBE, connect with Boyden: joined BAM, ultrasound + wireless probe at micron scales PoBAM group: 'every neuron at 1ms' – BRAIN Initiative
  12. 12. METHOD: EXAMPLE, PROTOTYPES EMERGING 'Neural Dust', 126um – 20um, 5um tail, ultrasound power & communication Animal trials in June 2014! MIT/Harvard: similar, with infrared 'RFID-like' system Kording: bio-vector 'pulled' nanowire array Cross-disciplinary 'hybrid' solutions toward a BrainNet
  13. 13. METHOD: EXAMPLE, BMI STRATEGY Long-term operational interfaces to very large number of neurons without harm to the brain Hi-Res BMI: In-Brain-Loop Use data otherwise inaccessible (sort memory) Deliver data otherwise impossible to generate (parameter fitting, super object recognition, etc.) Needs to understand brain circuit protocol (see Berger)
  14. 14. SUSTAINABLE: PIECE-WISE TO WBE Interfaces – Prostheses – WBE more feasible than 'clean-room' path Pieces, e.g. retina, hippocampus & small whole brains (drosophila 2018?) Sustainably to WBE – if a body attends to big-picture, iteratively deciding nudges
  15. 15. SUSTAINABLE: INCENTIVES FOR 'ARCHITECTING' Architecting: e.g. PoBAM & Carboncopies.org Personal experience of fragile support for cross-disciplinary big-picture (shared problem...) Grant funding encourages specialized silos Investment encourages short-term focus Long-term success probability linked to robustness Effort along multiple possible solutions + Sharing for hybrid solutions
  16. 16. SUSTAINABLE: ROBUST MISSION DESIGN No single points of failure: ● Technology ● Labs & People ● Resources for the work Technology & Labs & People well structured Frailty of resources continues to hamper predictable architecting (like carboncopies.org) Robustness: A 2014 goal.
  17. 17. SUMMARIZING SIM: Improve ourselves while we improve our machines Trends & exponential curves don't automatically lead to goals WBE monitored and nurtured: WBE is now lab-accepted Connectome proof-of-concept PoBAM – functional access 5 years to fruitfly WBE project? Robustness: Structural improvements needed! WBE Coffee Table Book

×