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I think what we talked about this week in class was really fascinating. I like the idea of a "score" that we have, that we then continually modify. But my only question is, if we have this motor symphony that we create through patterns of actions potentials...how is this different from an ideal, AI computer? When we talk about computers in class, we limit ourselves to the personal computers that we all use everyday. But this is only one type of computer. One of the main reasons why computers don't "learn" as we learn, I think, is because of the materials used. Wires that conduct current are limited, especially compared to living cells, with synapses and channels and proteins and plasticity, etc. However, when manufacturing and engineering gets even more precise, whose to say we can't engineer these?

What I think would be really interesting to delve deeper into though is the level of responsibility for action the central pattern generators have and the level that actual learning and experience plays. For example, we talked about birds that don't need to jump out of nests, but do. I don't know if a similar study has been conducted in humans (I can't imagine it would be very ethical to keep a baby tied down) but it would be interesting to see how much of that trial and error is actually necessary.