brain emulation won't work if we don't even know about some important circuit elements
scanning issues (if you don't scan it, you lose it), do we know all the neurotransmitters?, do we know all the channels? about 71 channel subunits from H. sapiens, combining in complicated ways, is the dynamic state of the brain important?
simulation issues (fixable later), are synapses everything? non-synaptic communication: diffusable messengers, glial cells, ephaptic effects, how important are neurogenesis and synaptogenesis?
(separate slides describing the technologies)
generally, a resolution of 5nm x 5nm x 50nm, achievable with electron microscopes
automatic slicing and microscopy, achievable with current technologies
similar to the human genome project in size and scope
depends on the scale of the simulation
estimates of brain computational power, memory, 10^16 bits (10^10 neurons, 1000 synapses, 34bit ID, 8 bit representation of state; Leitl 1995), 10^20 bits (microtubule memory; Tuszynski, 2006), 10^28 bits (10^11 neurons, 10^4 compartments, 4 dynamic variables and 10 parameters; Malickas, 1996), compare, all human knowledge until 2003: 5 exabyte = 10^19 bits, total Google storage: 1 exabyte (1 million servers x 1 Tb), CPU, 10^14 ops/s (10^10 neurons, 1000 synapses, 10 Hz; Freitas, 1996), 10^17 ops/s (10^11 neurons, 10^4 synapses, 100 Hz, 5 bits/signal; Bostrom, 1998), 10^14 ops/ (retina scale up; Merkle, 1989), 10^18 ops/s (10^11 neurons, 10^4 compartments, Hodkin-Huxley, 1200 FLOPS), compare, current supercomputers: 10^16 ops/s (top500.org)
more data, current simulations, (lots more), storage, memory, access times, disk storage, processing, MIPS over time (10x = 7.1 years), MIPS/# over time, computer performance per dollar over time, top 500
research usually consists of many steps and incremental improvements
it's useful to think about how to organize this cycle so that you achieve continuous improvement (think about it in your own work too)
the research cycle
which aspects of brain emulation research are reusable in other fields?, very large scale simulation, environment simulation, supercomputing, fault tolerance, virtual cell, brain, and body models for medical research
who might be motivated to fund some of this work?
what other applications provide economies of scale?
are there related consumer goods that might provide economies of scale? (gaming, household robotics, etc.)
it's a bad idea to start with solving the most complex problem right away; pick a model system instead
economic impact is important both for consequences of the research and funding
What would happen if you could "buy a mind", with or without attached arm?, $100m, $1m, $100k, $1000
Who is interested in funding it?
imaging, resolution, volume, functional information
image processing, geometric adjustment, data interpolation, noise removal, tracing
scan interpretation, parameter estimation, connectivity identification, synapse identification, cell type identification, databasing
providing adequate resources
physicalism - the mind is a purely physical phenomenon
Turing equivalence - there is no hypercomputation required in the brain
non-organicism - you don't need organic neurons to create a mind
scale separation - there is some scale below which the details of brain function can be abstracted as aggregate properties
scannability - all relevant properties can actually be scanned
brain-centeredness - all you really need for a mind is a brain (plus some I/O)
simulation = a computational model of some aspect of a system (not complete)
emulation = a full computational model of an entire system; all relevant properties are modeled
brain emulator = software running on non-neural hardware emulating the brain
mind emulator = brain emulator that succeeds at creating a mind
claim: we do not need to understand the system in order to emulate it
claim: a complete wiring diagram, plus knowledge of the state and properties of individual neurons should be sufficient
Q: is this reasonable? can you translate a piece of software or hardware without understanding it? how do you debug it?
levels of success
levels, parts list (neuron, glia, etc.), complete scan (full 3D scans at high resolution), brain database (combining the above into a wiring diagram), functional brain emulation (emulate the above generically, and produce some general properties of a brain), species-generic brain emulation (produce the full range of normally observed behaviors), social role-fit emulation (the simulation is accepted by others in at least some social roles; e.g. game avatar), mind emulation (the emulation experiences mental states like humans), personal identity emulation (the emulation describes itself as a continuation of the original mind)