Stathis Papaioannou wrote: > > Colin Hales writes: > >>> I understand your conclusion, that a model of a brain >>> won't be able to handle novelty like a real brain, >>> but I am trying to understand the nuts and >>> bolts of how the model is going to fail. For >>> example, you can say that perpetual motion >>> machines are impossible because they disobey >>> the first or second law of thermodynamics, >>> but you can also look at a particular design of such a >>> machine > and point out where the moving parts are going >>> to slow down due to friction. >>> >>> So, you have the brain and the model of the brain, >>> and you present them both with the same novel situation, >>> say an auditory stimulus. They both process the >>> stimulus and produce a response in the form of efferent >>> impulses which move the vocal cords and produce speech; >>> but the brain says something clever while the computer >>> declares that it is lost for words. The obvious explanation >>> is that the computer model is not good enough, and maybe >>> a better model would perform better, but I think you would >>> say that *no* model, no matter how good, could match the brain. >>> >>> Now, we agree that the brain contains matter which >>> follows the laws of physics. >>> Before the novel stimulus is applied the brain >>> is in configuration x. The stimulus essentially adds >>> energy to the brain in a very specific way, and as a >>> result of this the brain undergoes a very complex sequence >>> of physical changes, ending up in >>> configuration y, in the process outputting energy >>> in a very specific way which causes the vocal cords to move. >>> The important point is, in the transformations >>> x->y the various parts of the brain are just working >>> like parts of an elaborate Rube Goldberg mechanism. >>> There can be no surprises, because that would be >>> magic: two positively charged entities suddenly >>> start attracting each other, or >>> the hammer hits the pendulum and no momentum >>> is transferred. If there is magic - >>> actually worse than that, unpredictable magic - >>> then it won't be possible to model >>> the brain or the Rube Goldberg machine. But, barring magic, >>> it should be possible to predict the physical state >>> transitions x->y and hence you will know >>> what the motor output to the vocal cords will be and >>> what the vocal response to the >>> novel stimulus will be. >>> >>> Classical chaos and quantum uncertainty may make it >>> difficult or impossible to >>> predict what a particular brain will do on a >>> particular day, but they should not be a theoretical >>> impediment to modelling a generic brain which behaves in an >>> acceptably brain-like manner. Only unpredictable magical >>> effects would prevent that. >>> >>> Stathis Papaiaonnou >> I get where you're coming from. The problem is, what I am going to say >> will, in your eyes, put the reason into the class of 'magic'. I am quite >> used to it, and don't find it magical at all.... >> >> The problem is that the distal objects that are the subject about which >> the brain is informing itself, are literally, physically involved in the >> process. You can't model them, because you don't know what they are. All >> you have is sensory measurements and they are local and >> ambiguous....that's why you are doing the 'qualia dance' with EM fields - >> to 'cohere' with the external world. This non-locality is the same >> non-locality observed in QM and makes gravity 'action at a distance' >> possible. ..... I've been thinking about this for so long I actually have >> the reverse problem now...I find 'locality' really weird! I find 'extent' >> really hard to fathom. The non-locality is also predicted as the solution >> to the 'unity' issue. >> >> The empirical testing to verify this non-locality is the real target of my >> eventual experimentation. My model and the real chips will behave >> differently, it is predicted, because of the involvement of the 'external >> world' that is not available to the model. >> >> I hope to be able to 'switch off' the qualia whilst holding eveything else >> the same. The effects on subsequent learning will be indicative of the >> involvement of the qualia in learning. What the external world 'looks >> like' in the brain is 'virtual circuits' - average EM channels (regions of >> low potential that are like a temporary 'wire') down which chemistry can >> flow to alter synaptic weights and rearrange channel positions/rafting in >> the membrane and so on. >> >> So I guess my proclaimations about models are all contingent on my own >> view of things...and I could be wrong. Only time will tell. I have good >> physical grounds to doubt that modelling can work and I have a way of >> testing it. So at least it can be resolved some day. > > I'm not sure of the details of your experiments, but wouldn't the most direct > way to prove what you are saying be to isolate just that physical process > which cannot be modelled? For example, if it is EM fields, set up an > appropriately > brain-like configuration of EM fields, introduce some environmental input, > then > show that the response of the fields deviates from what Maxwell's equations > would predict. > > Stathis Papaioannou
I don't think Colin is claiming the fields deviate from Maxwell's equations - he says they are good descriptions, they just miss the qualia. Seems to me it would be a lot simpler to set up some EM fields of various spatial and frequency variation and see if they change your qualia. Brent Meeker --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Everything List" group. To post to this group, send email to everything-list@googlegroups.com To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/everything-list?hl=en -~----------~----~----~----~------~----~------~--~---