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Whole brain emulation
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=== Electron Microscopy === ==== SSET ==== By tilting the sample relative to the electron beam, the TEM can detect depth and create high-resolution 3D images<ref>Frank, 1992</ref><ref>Penczek, Marko et al., 1995</ref>. Due to the limitations on depth (1µm), it is useful mostly for scanning of 'local' tissue samples, ie the organelles and cellular structures of small volumes of tissue.<ref>Lučić, Förster et al., 2005</ref> ==== SSTEM ==== '''Serial Section Transmission Electron Microscopy''' By making ultrathin slices, a three-dimensional model can be made. This method has been used to build a model of a neuromuscular juncture (50nm-thick sections)<ref>Tsang, 2005</ref> and to construct the connectome of the ''C. Elegans''<ref>White, Southgate et al., 1986</ref>. However, this process is labor intensive unless it can be automated. ==== SBFSEM ==== One way of reducing the problems of sectioning is to place the microtome inside the microscope chamber (Leighton, 1981) for further contrast, plasma etching was used (Kuzirian and Leighton, 1983) (Denk and Horstmann, 2004) demonstrated that backscattering contrast could be used instead in a SEM, simplifying the technique. They produced stacks of 50‐70 nm thick sections using an automated microtome in the microscope chamber, with lateral jitter less than 10 nm. The resolution and field size was limited by the commercially available system. They estimated that tracing of axons with 20 nm resolution and S/N ratio of about 10 within a 200 μm cube could take about a day (while 10 nm x 10 nm x 50 nm voxels at S/N 100 would require a scan time on the order of a year). Reconstructing volumes from ultrathin sections faces many practical challenges. Current electron microscopes cannot handle sections wider than 1‐2 mm. Long series of sections are needed but the risk of errors or damage increase with the length, and the number of specimen holding grids becomes excessive (unless sectioning occurs inside the microscope (Kuzirian and Leighton, 1983)). Current state of the art for practical reconstruction from tissue blocks is about 0.1 mm3 , containing about 107‐108 synapses (Fiala, 2002). ==== FIBSEM ==== The semiconductor industry has long used focused ion beams to perform failure analysis tests on integrated circuits. [http://www.fei.com/ FEI] researchers have shown that this can be used to image [[#Plastination|plastinated]] neural tissue. An ion beam ablates the top 30 to 50 nanometers of a 100x100μm tissue sample. The backscatter is imaged by the SEM, and the process is then repeated. It is similar to SBFSEM, but without the problems caused by high beam current. ==== 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.
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