Редактирование: Whole brain emulation (раздел)

==== Increasing Speed of SEM ====

From the above discussion it is clear that long imaging times constitute a major barrier to 
whole brain emulation using SEM techniques. However, there is currently a major research 
push toward massively parallel multi‐beam SEMs which has the potential to speed up SEM 
imaging by many orders‐of‐magnitude. This research push is being driven by the 
semiconductor industry as part of its effort to reduce feature sizes on computer chips below 
the level that traditional photolithography can produce.  
 
The circuitry patterns within computer chips are produced through a series of etching and 
doping steps. Each of these steps must affect only selected parts of the chip, so areas to be left 
unaffected are temporally covered by a thin layer of polymer which is patterned in exquisite 
detail to match the sub‐micron features of the desired circuitry. For current mass production 
of chips this polymer layer is patterned by shining ultraviolet light through a mask onto the 
surface of the silicon wafer which has been covered with the photopolymer in liquid form. 
This selectively cures only the desired parts of the photopolymer. To obtain smaller features 
than UV light can allow, electron beams (just as in a SEM) must instead be used to selectively 
cure the photopolymer. This process is called e‐beam lithography. Because the electron beam 
must be rastered across the wafer surface (instead of flood illuminating it as in light 
lithography) the process is currently much too slow for production level runs. 
 
Several research groups and companies are currently addressing this speed problem by 
developing multi‐beam e‐beam lithography systems (Kruit, 1998; van Bruggen, van Someren 
et al., 2005; van Someren, van Bruggen et al., 2006; Arradiance Inc). In these systems, 
hundreds to thousands of electron beams raster across a wafer’s surface simultaneously 
writing the circuitry patterns. These multi‐beam systems are essentially SEMs, and it should 
be a straightforward task to modify them to allow massively parallel scanning as well 


(Pickard, Groves et al., 2003). For backscatter imaging (as in the SBFSEM, FIBSEM, and 
ATLUM technologies) this might involve mounting a scintillator with a grid of holes (one for 
each e‐beam) very close to the surface of the tissue being imaged. In this way the interactions 
of each e‐beam with the tissue can be read off independently and simultaneously. 
 
It is difficult to predict how fast these SEMs may eventually get. A 1,000 beam SEM where 
each individual beam maintains the current 1 MHz acquisition rate for stained sections 
appears reachable within the next ten years. We can very tentatively apply this projected SEM 
speedup to ask how long imaging a human brain would take. First, assume a brain were 
sliced into 50nm sections on ATLUM‐like devices (an enormous feat which would itself take 
approximately 1,000 machines – each operating at 10x the current sectioning rate – a total of 
3.5 years to accomplish). This massive ultrathin section library would contain the equivalent 
of 1.1∙1021 voxels (at 5×5×50 nm per voxel). Assuming judicious use of directed imaging 
within this ultrathin section library only 1/10 may have to be imaged at this extremely high 
resolution (using much lower, and thus faster, imaging on white mater tracts, cell body 
interiors etc.). This leaves roughly 1.1∙1020 voxels to be imaged at high resolution. If 1,000 
SEMs each utilizing 1,000 beamlets were to tackle this imaging job in parallel their combined 
data acquisition rate would be 1∙1012 voxels per second. At this rate the entire imaging task 
could be completed in less than 4 years.