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
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Received on Sun Dec 17 2006 - 02:02:33 PST