[Udo]

It's not about complexity or raw computational power, it's about functionality. One area where brain research still struggles to model the basics is how the brain actually integrates information over time, and how internal models and representations are formed.

The "classical" synaptic response model was always good at explaining basic signal transmission, but it was essentially stateless. Now we know that neurons are far from stateless, there is extensive chemical modification going on working at different timescales and I guess this "new" discovery is also an important piece that was missing from the standard model. It may explain advanced neuronal states that surpasses simple chemical sensitization and suppression - and it may also provide hints about how feedback works in learning and building internal representations.

ANNs and other AI techniques are getting very good and efficient, but one reason why general artificial intelligence (as in artificial persons) continues to escape us is that we still don't have a good model how the brain organizes and improves itself to form a consistent but autonomously adapting unit which can rightfully be called a mind. I hope that AI people can use these pointers provided by bio research and advance toward this goal.