about a paper that as far as I can tell is still embargoed, but will be out on PNAS within a week.

Just released.

Abstract:

It is well-established that synapse formation involves highly selective chemospecific mechanisms, but how neuron arbors are positioned before synapse formation remains unclear. Using 3D reconstructions of 298 neocortical cells of different types (including nest basket, small basket, large basket, bitufted, pyramidal, and Martinotti cells), we constructed a structural model of a cortical microcircuit, in which cells of different types were independently and randomly placed. We compared the positions of physical appositions resulting from the incidental overlap of axonal and dendritic arbors in the model (statistical structural connectivity) with the positions of putative functional synapses (functional synaptic connectivity) in 90 synaptic connections reconstructed from cortical slice preparations. Overall, we found that statistical connectivity predicted an average of 74 ± 2.7% (mean ± SEM) synapse location distributions for nine types of cortical connections. This finding suggests that chemospecific attractive and repulsive mechanisms generally do not result in pairwise-specific connectivity. In some cases, however, the predicted distributions do not match precisely, indicating that chemospecific steering and aligning of the arbors may occur for some types of connections. This finding suggests that random alignment of axonal and dendritic arbors provides a sufficient foundation for specific functional connectivity to emerge in local neural microcircuits.

As best I can make out, the PR is claiming that someone can "make a near perfect prediction" of something that it simultaneously claims results from synapses that "randomly bump into each other". Hm, okay.

It's like describing as "a near perfect prediction", the prediction that a tossed coin will come down heads with 50% probability. The 50% figure may be really precise, but that still tells you nothing about the next coin toss. The press release seems to confuse knowledge about a distribution with knowledge about individuals drawn from it.

As I understand it, what the paper, and Henry Markram as quoted in the press release, are actually saying is that their experiments show a distribution of connections that one would get by things randomly bumping into each other. This implies the predictions that there is no other organising mechanism in play yet to be discovered, and that to build an artificial network capable of the same functionality, one can build the connections in the same random manner. Or as they put it in the title, "Statistical connectivity provides a sufficient foundation for specific functional connectivity".

Note that the title is a prediction from what they have observed, not the observation itself. Functional comparisions of real neural tissue and artificial networks constructed on these lines have not yet been done.

Personally, I would assume that it would be quite difficult for a random distribution of neurons to form the exact same network of synapses 85% of the time. Two random graphs with the same number of vertices have a very low probability of being isomorphic, but the spanning trees of those random graphs would have a trivial isomorphism and I assume neural networks formed by synapses randomly bumping into each other are more like the union of a few random spanning trees (lots of local connections, fewer long ones) than fully random graphs. Still, it's probably not 85% or 95% likely for there to be an isomorphism. However, if the shape of the neurons is what determines the properties of the synapses then it may be that how the synapses grow isn't as important as how the types of neurons are initially distributed. I haven't read the paper either, but if the summary is correct they distributed the different types of neurons "randomly", which of course doesn't say if there was a complex probability density over the 3D space or if it was, e.g., uniform probability for each neural shape.