In my first post, I argued that 1) to understand a complex organized system, one needs to understand the organization rather than have a detailed description of the structure, 2) an incomplete or imprecise measurement of structure, as is necessarily the case with any physical measurement, does not in general convey the functionality of the system. In his reply, Bernhard Englitz rightly argued that the knowledge of the connectome is nonetheless useful. I do not disagree with that claim, and I do believe that connectomics is certainly a great neuroanatomical tool. So the question is: what can and what cannot offer the knowledge of the connectome?
First of all, a quick comment. Bernhard complained that connectomics is often portrayed as an extreme claim. I was only referring to published texts by supporters of connectomics. One is Seung's book, Connectome. Arguably, this is a popular science book so I agree that the claims in the book may be overstated for the sake of communication. But there are also articles in peer-reviewed journals, which I think make quite similar claims, for example “Structural neurobiology: missing link to a mechanistic understanding of neural computation”, Nature Rev Neuro (2012), by Denk, Briggman and Helmstaedter. The basic claim in that text and in Seung's book is that there is a strong relationship between structure (specifically, connectome) and function, and implicitly that connectionism provides an adequate account of neural function. For example, both the paper above and Seung's book envisage the reading of memories from the connectome as a distinct possibility (I wouldn't say that they make a strong claim, but they certainly consider it as a reasonable possibility). I wouldn't necessarily qualify this view as extreme, but I simply do not think that the structure-function relationship is so strong in this case.
In this post, I want to address a particular comparison that is often used to emphasize the potential of connectomics: the comparison between connectomics and genomics, in particular the human genome project. This comparison is also used by other large initiatives, for example the Human Brain Project. There is no doubt that the human genome project was useful, and that sequencing entire genomes is a very useful tool in genomics. But what about the relationship between structure and function? How do you know, for example, the function of a particular gene that you have sequenced? You would know by manipulating the gene (e.g. knock-out) and looking at functional changes in the organism; or you would examine a large database of genomes and look for correlates between that gene and function (for example pathologies). In both cases, function is observed in the organism, it is not derived from the knowledge of the genome. As far as I know, we don't know how to predict the function of a gene from its DNA sequence. So even if there were a one-to-one relationship between structure (DNA) and function, the knowledge of the structure would not tell us what that relationship is and so it would not tell us the function. In addition to this, we know that the relationship between structure and function is not one-to-one in the case of the genome: this is what epigenetics is all about (and so the example of genomics is completely in line with the arguments of my first post).
So, if the structure-function relationship is similarly strong in connectomics as in genomics, then 1) the connectome itself will provide little direct insight into brain function, 2) insight might come from correlating connectomes and the function of brains (in a yet to be specified way), 3) the connectome will not determine brain function. In particular, point (3) makes it quite unlikely that memories can be inferred from the connectome. I would also like to point out that a complete comparison with genomics regarding point (2) requires the possibility not only to measure the connectome but also to finely manipulate the connectome and observe functional changes in living organisms. I do not see how current connectomics technologies (electron microscopy) could make it possible. There is a critical limitation, at least for the foreseeable future, which is that the connectome can only be measured on dead organisms, in contrast with DNA sequencing, which greatly limits the possibilities of connectome manipulation or diagnosis based on (detailed) connectome.
Finally I want to point out that the structure-function relationship is likely to be weaker in connectomics than in genomics. First, there is a fundamental difference: the DNA is a discrete structure (4 bases), the connectome is not, if you consider synapse strength. So it should be possible to exactly measure the graph of connectivity in the same way as you can sequence DNA, but measuring the extended connectome (with synaptic strength or delays) can only be measured with limited precision. A second, probably more serious difference, is that while there is a concept of gene that has some functional unity and correspond to a well-identified portion of the genome, there is no equivalent concept in the connectome. In genomics, one can knock-out a gene or look for structure-function correlates for different versions of the same gene. In connectomics, there is in general no similarly well-defined portion of the connectome that can be identified across individuals. This might be partially possible when considering connections made onto well-identified sensors and effectors (say, in the retina), but comparing cortical connectomes across individuals is another story.
So connectomics suffers from the same problems about structure-function relationship as genomics, but quite a bit worse. Again I am not saying that it is not a useful set of tools. But it is just this: additional measurement tools in the hands of neuroscientists, not fundamental data that would specify or in general even suggest brain function. One example where it might be quite useful is in finding new markers of neurological disorders. It has been hypothesized that some neurological diseases are “connectopathies”, ie are due to abnormal connections. Here as in genomics, one could compare the connectomes of subjects that have suffered from those diseases and of control subjects and perhaps identify systematic differences. Whether those differences are correlates of the disease or have a more causal role in the disease, such an identification could certainly help understand the origins and mechanisms of the pathologies. This is a completely different claim than saying that brain function can be understood from the connectome: in this case brain function is observed at the functional level, and simply correlated with some particular element of structure, it is not the structure itself that informs us of function.
In summary: 1) the structure-function relationship is not that strong in genomics and is certainly weaker in connectomics, and more importantly the structure-function relationship is unknown, 2) connectomics is more limited as a set of tools than genomics, 3) what we should expect from connectomics is not so much the possibility to infer brain function from connectome as to correlate some aspects of brain function or dysfunction with connectomes.