Summary We have [relatively] recently scanned the whole fruit fly brain, simulated it, confirmed it is pretty highly constrained by morphology alone. Other groups have been working on optical techniques and genetic work to make the scanning process faster and simulations more accurate. Fruit Flies When You’re Having Fun The Seung Lab famously mapped the fruit fly connectome using serial section electron microscopy. What is underappreciated is that another group used this information to create a whole brain emulation of the fruit fly. Now, it used leaky integrate and fire neurons and did not model the body of the fly, but it is still a huge technical achievement. The first author has gone off to work at Eon Systems, which is very explicitly aimed at human whole brain emulation. They did some cool things in the simulation. One is that they shuffled the synaptic weights to see how much that changed the neural activity. Turns out, quite a bit. This is a good thing because it means they’re probably right about how synaptic weight manifests in morphology. > Although modelling using the correct connectome results in robust activation of MN9 in 100% of simulations when sugar-sensing neurons are activated at 100 Hz, only 1 of 100 shuffled simulations did (Supplementary Table 1d). Therefore, the predictive accuracy of our computational model depends on the actual connectivity weights of the fly connectome. I would recommend reading the whole paper. I think I would do it a disservice by giving an intermediate level of detail in a summary. They just got mind-blowingly good results for such a simple model and it really gives me hope that the actual simulation aspect is a much more tractable problem than I once thought[1]. Connectome Tracing Now And The Near Future The two biggest issues with connectome tracing right now are speed and accuracy. It takes a long time to image all the samples and is very costly to parallelize the process because electron microscopes are expen