Here is what I just posted to the epic thread on Connectionists:
The original complaint in this thread seems to be that the main problem of (computational) neuroscience is that people do not build upon the work of others enough. In physics, no one reads the original works of Newton or Einstein, etc., anymore. There is a set canon of knowledge that everyone learns from classes and textbooks. Often if you actually read the original works you’ll find that what the early greats actually did and believed differs from the current understanding. I think it’s safe to say that computational neuroscience has not reached that level of maturity. Unfortunately, it greatly impedes progress if everyone tries to redo and reinvent what has come before.
The big question is why is this the case. This is really a search problem. It could be true that one of the proposed approaches in this thread or some other existing idea is optimal but the opportunity cost to follow it is great. How do we know it is the right one? It is safer to just follow the path we already know. We simply all don’t believe enough in any one idea for all of us to pursue it. It takes a massive commitment to learn any one thing much less everything on John Weng’s list. I don’t know too many people who could be fully conversant in math, AI, cognitive science, neurobiology, and molecular biology. There are only so many John Von Neumanns, Norbert Wieners or Terry Taos out there. The problem actually gets worse with more interest and funding because there will be even more people and ideas to choose from. This is a classic market failure where too many choices destroys liquidity and accurate pricing. My prediction is that we will continue to argue over these points until one or a small set of ideas finally wins out. But who is to say that thirty years is a long time. There were almost two millennia between Ptolemy and Kepler. However, once the correct idea took hold it was practically a blink of an eye to get from Kepler to Maxwell. However, physics is so much simpler that neuroscience. In fact, my definition of physics is the field of easily model-able things. Whether or not a similar revolution will ever take place in neuroscience remains to be seen.
