________________________________ From: meekerdb meeke...@verizon.net
[snip] >> Although reductionism has recently received a lot >> of bad press from supermarket tabloids and new age >> gurus the fact remains that if you want to study >> something complex you've got to break it into >> simpler parts and then see how the parts fit >> together. And in the final analysis things >> happen for a reason or they don't happen for a >> reason; and if they did then it's deterministic and >> if they didn't then it's random. Perhaps your final analysis is a bit too shallow and self limiting. Why you cling so tenaciously to this need for definitive causality chains (or else it must be complete randomness) is amusing, but is not misguided. You cannot show definitive causality for most of what goes on in most of the universe. You can hypothesize a causal relationship perhaps, but you cannot prove one for all manner of phenomenon arising out of chaotic systems. The brain is a noisy chaotic system and you are attempting to impose your Newtonian order on it. Your approach does not map well onto the problem domain. And what you say has no predictive value; it does not help unravel how the brain works... or how the mind arises within it. >> It does help. There's no evidence that the brain can't be understood as >> a parallel computer plus some randomness. The problem with John's >> formulation is he insists there is either *a* reason or not *a* reason. >> Hardly anything can be thought of as having *a* reason. In the case of >> human behavior, each instance almost certainly has many different causes, >> some in memory, some in the immediate environment, and some which are >> random and don't have an effective cause. I think of the person, >> brain/body/etc, plus immediate environment narrow down the probable >> actions to a few, e.g. 1 to 20, and then some quantum randomness realizes >> one of those. So it's not deterministic like Laplace's clockwork world, >> but it's not anything-is-possible either. Sure reductionist approach can gain you a partial understanding; you can slice the brain up; analyze processes and try to classify and drill down to smaller and down into increasingly tightly focused problem domains within the larger problem domain of how the brain works. But this approach fails to capture the holistic dynamic processes and subtle interplays between rapidly forming and also rapidly subsiding synchronized firing networks that pull together coalitions of neurons from many different brain regions. The brain is not only massively parallel -- it is a superbly tight packed one hundred trillion connection machine with 86 billion operating nodes in the network -- it is also incredibly noisy and seemingly chaotic. The simple deterministic causality approach cannot model a vastly parallel and very noisy chaotic system such as the brain. The brain is not operating on deterministic principles -- or at least not completely so. Without modeling the chaos -- and chaos is modeled all the time and predictive statements can be made about chaotic systems (say the chaotic airflow over an air foil for example). But these models and the equations that comprise them account for chaos and often rely on probabilistic and consensus based algorithms. I am not arguing that the brain is beyond study or cannot be understood, analyzed or modeled. What I am arguing is that it is not a simple deterministic system in which state X will always lead to outcome Y; nor can it always be determined based on knowing an outcome Y in the brain what the causational state was that ultimately lead to that outcome. Even if there may be causation the processes by which the brain operates are so distributed and inter-dependent and the system is so incredibly noisy (and it really is a very high noise to signal ratio) that any attempt to work backwards from some outcome down the causal chain of neural activity that resulted in it rapidly breaks down and grows geometrically more difficult with each remove from the final result and back into the densely nested forest of potential network branches. John keeps insisting that X is Y or X is not Y. True, but so what? It does not provide any great insight into how the brain works as a dynamic entity. Basically based on reading his posts on the subject what I am stating is that he would not be hired to help work out the problem based on his views of how the brain can be understood. In fact he would not make it past the initial screening interview -- IMO. I am not calling him stupid -- though he does question my intelligence -- but for some reason (which I know not of) he clings to this simplistic view of what is in fact a highly dynamic, noisy, chaotic and vastly parallelized system. Cheers, Chris [snip] -- You received this message because you are subscribed to the Google Groups "Everything List" group. To unsubscribe from this group and stop receiving emails from it, send an email to everything-list+unsubscr...@googlegroups.com. To post to this group, send email to everything-list@googlegroups.com. Visit this group at http://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/groups/opt_out.