An individual’s “connectome” (Sporns, Tonino, & Klötter, 2005; Hagmann, 2005) is in essence a mathematical object that describes all the neural connections in a nervous system. The word was coined by Olaf Sporns et al. in their 2005 paper and independently by Patric Hagmann in his doctoral dissertation. Sporns describes the 2005 paper as a “manifesto” outlining an ambitious research program in support of a model linking structure and function that the authors felt would have a profound impact on how we understand the brain. (The following excerpts are from Sporns’ 2010 talk at the Allen institute; the full video is embedded in references.)
We had no information until just a few years ago about similar data [about brain networks] from the human brain. That was a big gap in our understanding of the human brain because we had no good structural model for it. We had a lot of imaging data . . . But it’s very difficult to interpret imaging data if you have no structural model by which it is generated. (Allen Institute, 2010)
Since 2005, data-driven research on the connectome (some of which is under the auspices of the NIH Human Connectome Project) is now being conducted at multiple scales: micro (“single neurons and synapses”), meso (“brain regions and pathways”), and macro (“neuronal populations and their interconnecting circuitry”) using different imaging technologies.
Implications for Psychiatry
What is particularly attractive about the concept of a connectome vis-a-vis psychiatry is that it “naturally fits within a larger theoretical framework and thus links neuroscience to modern developments in network science and complex systems” (Sporns, 2011). In other words, it grounds a longstanding intuition that the brain in general and psychiatric disorders in particular reflect continuous interactions of biological and sociocultural systems (Kirmayer, 2012).
In the network science field, in other contexts – internet, social networks, epidemiology – perturbations of networks are very important to study because people want to know what happens when we lesion the network, what happens when we disrupt its functionality in terms of the global outcomes that result. I think we have a similar question on the horizon here for these neurological, psychiatric conditions. What is it about the brain that has changed in terms of its network architecture that brings about – or is involved or at least associated with – the function that is being perturbed. (Allen Institute, 2010)
A second factor is its ability to account for plasticity (and individual differences). This is because while, on the one hand, the connectome constrains neural activity – Sebastian Seung (2012) likens it to a streambed that organizes the flow of water  (and Sporns calls it a “structural skeleton”), on the other neural activity (thoughts, feelings, and perceptions) over time can change the connectome.
If we have a structural model of the human brain we can actually damage it in the computer. And we can ask questions about how impactful are certain lesions that we make inside this computational model. We make these lesions by deleting a number of nodes and their connections. And we then observe how the dynamics – in a forward computing sense – of the human brain changes as a result of making these lesions. We can then compare our empirical data to data that is obtained from people with stroke and we can ask questions about recovery. What is it about the metrics of global brain connectivity, functional interactions that changes in a good outcome scenario and is there anything we can do on an interventional level with therapeutic or other interventional means that can guide brain repair and recovery in a good direction. The brain really is a complex network. If we make a lesion in our model in any particular spot, it’s not just that that spot is lost, and the rest of the brain just goes on doing what it’s doing, all relationships across all other nodes in the brain change, and that’s because the brain responds as a whole. This is something that becomes very plastic and very graspable if you do computational modeling and it really opens up new horizons . . . for understanding the functional impact of lesions and perhaps other disease states as well. (Allen Institute, 2010)
 Computational neuroscientist Sebastion Seung (MIT), who is studying the connectome from the neuron’s eye view, gave an exuberant talk on the connectome at one of the Ted conferences, and now he’s written an exuberant book on the subject that is, seriously, a page turner that concludes with a section on cryonics and “the ultimate cyber-fantasy” of uploading your brain and “living happily ever after as a computer simluation” (2012, xxi).
Hagmann, P. (2005) From diffusion MRI to brain connectomics (Doctoral dissertation). École Polytechnique Fédérale de Lausanne (EPFL), Lausanne.
Seung, S. (2012). The connectome: How the brain’s wiring makes us who we are. New York: Houghton Mifflin Harcourt.
Allen Institute (2010). Olaf Sporns: 2010 Allen Institute for Brain Science Symposium. Retrieved 21 February 2012 from http://www.youtube.com/watch?v=oikjPdV7LbU
Sporns, O. (2011). The human connectome: A complex network. Annals of the New York Academy of Sciences, 1224, 109–125.
Sporns, O., Tononi, G., & Kötter, R. (2005). The human connectome: A structural description of the human brain. PLoS Computational Biology, 1(4), e42. doi:10.1371/journal.pcbi.0010042