Редактирование: Whole brain emulation (раздел)

== Map of Technological Capabilities ==

[[File:WBE_Capabilities_map.png|thumb|center|400px]]

'''Driving forces for the development of the technology:'''

* <span style="background-color:#33FF99;">Moore's Law</span>
* <span style="background-color:#CCFF66;">Commercial</span>
* <span style="background-color:#FF9933;">Research</span>
* <span style="background-color:#CC3300;">WBE Specific?</span>

{| border="1" align="center" style="text-align:center;" class=wikitable
! colspan="3" | Capability || Description || Status
|-
|rowspan="5" | Scanning || colspan="2" | Preprocessing/fixation || align="left" | Preparing brains appropriately, retaining relevant microstructure and state. || align="left" | See [[Cryonics]], [[Plastination]], but overall fairly good.
|-
| colspan="2" | Physical handling || align="left" | Methods of manipulating fixed brains and tissue pieces before, during, and after scanning. || align="left" | ATLUM automates slicing, and there's been some work in automating the feeding of tape into a machine that sprays contrast metals on it and then passes it under an electron microscope.
|-
| rowspan="3" | Imaging || Volume || align="left" | Capability to scan entire brain volumes in reasonable time and expense. || align="left" | Massively parallel ATLUM and massively parallel scanning electron microscopes. The latter are being developed by the semiconductor industry.
|-
| Resolution || align="left" | Scanning at enough resolution to enable reconstruction. || align="left" | Electron microscopy has provided sub-nanometer resolution since before the 1950's. Electron microscopes at that resolution may cost well above half a million dollars, though.

|-
| Functional information || align="left" | Scanning is able to detect the functionally relevant properties of tissue. || align="left" | The software to translate electron micrographs to abstract models is currently in very early stages, capable of tracing the shape of cells, but not much more.

|-
|rowspan="10"| Translation || rowspan="4" | Image processing || Geometric adjustment || align="left" | Handling distortions due to scanning imperfection. || align="left" | Can't be much of a situation (Some basic image recognition to sense overlap and matching of the electron micrographs).

|-
|Data interpolation || align="left" | Handling missing data (Using surrounding data to interpolate what should be placed in missing spots). || align="left" | Unknown.
|-
| Noise removal || align="left" | Improving scan quality. || align="left" | Can't be much of a situation.
|-
| Tracing || align="left" | Detecting structure and processing it into a consistent 3D model of the tissue. || align="left" | Doable right now. Shape tracing is possibly the simplest, cheapest part of the whole process.

|-
| rowspan="4" | Scan interpretation || Cell type identification || align="left" | Identifying cell types. || align="left" | The software to translate electron micrographs to abstract models is currently in very early stages, capable of tracing the shape of cells, but not much more.

|-
|Synapse identification || align="left" | Identifying synapses and their connectivity. || align="left" | The software to translate electron micrographs to abstract models is currently in very early stages, capable of tracing the shape of cells, but not much more.

|-
| Parameter estimation || align="left" | Estimating functionally relevant parameters of cells, synapses, and other entities. || align="left" | The software to translate electron micrographs to abstract models is currently in very early stages, capable of tracing the shape of cells, but not much more.

|-
| Databasing || align="left" | Storing the resulting inventory in an efficient way. || align="left" | This is essentially a hardware problem. The scan of a mere nematode produces whole terabytes of electron micrographs. There have to be stored for interpretation (Unless one interprets them during the scan), but the abstract model may be much lighter and easier to store.

|-
|rowspan="2" | Software model of neural system || Mathematical model || align="left" | Model of entities and their behaviour (The simulator itself). || align="left" | Pick one.

|-
| Efficient implementation || align="left" | A final, fast implementation of the model (For example, neuromorphic hardware or dedicated chips where the algorithms are implemented directly in the hardware). || align="left" | The [[Izhikevich model of spiking neurons|Izhikevich model]], with considerations. (Actually, Izhikevich already analyzed the implementation of the model in MEMS).

|-
|rowspan="6"| Emulation || colspan="2" | Storage || align="left" | Storage of original model and current state (And whatever snapshots may be made). || align="left" |  Again, a hardware problem.

|-
| colspan="2" | Bandwidth || align="left" | Efficient inter‐processor communication (Long-range data buses to implement long-range axons). || align="left" | Unsure.

|-
| colspan="2" | CPU || align="left" | Processor power to run simulation. Moore's Law can't be expected to continue beyond the first half of this century. Processors can't exponentiate forever, because of this, alternative computing has to be used: Instead of running the simulation as a program in a Universal Computer (An ordinary computer), it should be done with Neuromorphic hardware: The model is implemented directly as hardware. One chip, one neuron (Or one compartment, or one minicolumn, as the case may be), mounted on some kind of routing system. || align="left" | Not even close... Well, technically we can already emulate an entire brain of Izhikevich neurons, and the original emulation was done on a Beowulf with 27 processors, so a bigger, badder computer could probably get the slowdown factor a little into the acceptable zone.

|-
| colspan="2" | Body model || align="left" | Simulation of body enabling interaction with virtual environment or through robot. || align="left" | Shouldn't be much of a situation.

|-
| colspan="2" | Environment model || align="left" | Virtual environment for virtual body. || align="left" | Can't be much of a situation, if it's visual only. A collision checker may provide some basic pressure to sensory neurons.

|-
| colspan="2" | Exoself || align="left" | A software object that holds the simulation, maps sensory/motor neurons to the body model, ties the model to a virtual body in the virtual environment or to a telepresence robot, and handling communication with the network and the operating system. || align="left" |  Once the above are ready, write a wrapper that puts them all together, and you have an Exoself.
|}