Current scientific consensus is that connections between neurons are specific and based on neuron type, instead of being randomly distributed. Often this connectivity is inferred statistically, but this is haphazard and it would be much easier if the specific neural circuits could be mapped. Brigmann and Denk reviewed the extant attempts to make this happen back in 2006.
They note that since unmyelinated axons are about 100 nanometers in diameter and the thinnest parts of dendrites are about 50 nanometers, the resolution on the scanner must be minute. The only scanning technology currently capable of such a resolution is electron microscopy. Following staining with electron dense atoms on the region of interest, here are three methods that they discuss:
1) Serial section transmission electron microscopy. This is the oldest method, in which thick blocks of tissue are fixed in some sort of material (i.e., an aldehyde) and then cut into sections with a gem quality diamond knife on an ultramicrotome. These ribbon-like sections are transferred to the microscope, which records contrast based on higher elastic scattering of electrons in places where the electron dense atoms (i.e., the heavy metal) are more highly concentrated. It is this method which was used to map the entire neural circuitry of C. elegans, all 302 neurons and 5000 (!) chemical synaptic connections, using around 8000 serial sections that were each 50 nms thick. The problems with the technique are uneven section thickness, a lack of automation, geometrical distortion, debris found on the sections, and, perhaps most important, time constraints. The C. elegans study took 15 years to complete and that wasn’t even a very large volume of tissue, so more ambitious projects like in mice would likely require a more automated method to ensure feasibility.
2) Serial block-face scanning electron microscopy. This technique uses a custom microtome in a low-vacuum scanning electron microscope chamber to automate the sectioning and imaging of blocks of tissue. The images are formed based on electron scattering on the surface of an embedded tissue sample (i.e., the block face) before they are cut. They can achieve a lateral resolution of about 30 nm. The sections are then cut with an oscillating diamond knife. Hundreds of sequential sections can be imaged and cut this way with a thickness of only 30 nm each. Because the images are already aligned it is easier to automate the data analysis using a machine learning algorithm. Computational storage may actually be issue here, but in Moore’s Law we trust.
3) Serial section electron tomography. This technique uses multiple 2-d projections at various angles to reconstruct 3-d structure of the given tissue. Block tissues are sectioned relatively thickly (0.5-3 micrometers), and sections are imaged using high-voltage transmission electron microscopy at 1–2° increments. The advantage of this technique is that fewer tissues have to be damaged. The downside is that the tissue may be distorted and shrunk by the high energy electrons, but this can be mitigated with energy filtering techniques, which ultimately allows for a scanning resolution of 10 nm.
Brain scanning at a low level of resolution will constrain theories and allow for an amazing interplay between genetics, behavior, and circuitry. Of course it is not the last step–people still study C. elegans in droves, and for good reason! But when I look around at all of the avenues of research in neuroscience today, this seems to be one of if not the most important.
Briggman KL, Denk W. 2006 Towards neural circuit reconstruction with volume electron microscopy techniques. Current Opinion in Neurobiology 16:562-570. doi:10.1016/j.conb.2006.08.010.