craig@unicus.UUCP (06/06/87)
Forgive the wide cross posting, net.gods, but I am interested in gathering an opinion from biological and artifical intelligence people on a model that arises from AI but has (possibly) biological implications: Foreword or WHY I'M WRITING THIS. -------------------------------- I was semi-surprised in recent months to discover that cognitive psychology, far from developing a bold new metaphor for human thinking, has (to a degree) copied at least one metaphor from third-generation computer science. This description of the human memory system, though cloaked in vaguer terms, corresponds more or less one-to-one with the traditional computer architecture we all know and love. To wit: - senses have "iconic" and "echo" memories analogous to buffers. - short term memory holds information that is organized for quick processing, much like main storage in a computing system. - long term memory holds information in a sort of semantic association network where large related pieces of information reside, similar to backing or "archived" computing storage. At least this far, this theory appears to owe a lot to computer science. Granted, there is lots of empirical evidence in favour, but we all know how a little evidence can go far too far towards developing an analogy. What I think we may need are good parallel connectionist computing models for the social sciences to copy, rather than these old ones that we are beginning to fuse and modify and discard. After all, engineering can construct and test artifacts much quicker than psychologists can. And investigate their insides and their performance as well... The Point or WHAT I'M THINKING ABOUT ------------------------------------ Single cells are constructed according to instructions resident in their own DNA. When their reproductive process fails, they die, become cancerous, etc... In computing terms, a self-reproducing program messes up the code and therefore fails to function (it does not reproduce). Or, it may continue to reproduce a flawed cell (cancer...). But a biological mechanism such as, say, a muscle or a brain is a massively parallel system consisting of many many redundant cells, each of which is capable of performing (at least almost) the same function. So many many parts would have to fail before the effect was enough to endanger the system as a whole. That is, it degrades gracefully. This effect has been observed in parallel sensing systems, which use several low-resolution phased fields that redundantly cover the same area. Removing one such field results in a loss of resolution, but not utter failure to detect a stimulus. Details in Geoffrey Hinton and others... (Byte AI issue, 1985?) At some point of degradation, the whole parallel system will collapse. Or an aged human being will die of a cold. The Question or WHAT DO YOU THINK? ---------------------------------- Apparently, all human organ weights begin to decline shortly after puberty. The cumulative effect of this seeming reduction of resources isn't felt so strongly until middle-age, when we become more susceptible to disease. So far, this is just a statement of the nature of parallel systems. But does it hold up as a theory of aging? - Is mitosis sufficiently prone to failure to account for organ decline? - Statistically, one would expect exponential distribution for failure of single cells, the rate dependent on mitosis failure, and perhaps modified by other cell-killing factors - Does organ failure, medically, occur at the point where a parallel processing system, mathematically, would fail? I've heard that mammal cells appear to suffer a "hard" reproductive limit of 52 mitosis operations, and that meiosis "resets this counter" to 0. - any comment on this, bio-med types? Is it true? - Would a theory assuming a simple variable or random "counter" in each cell limiting its reproductive span better explain aging (programmed cells...) It doesn't seem so... regardless of the origin of the failure, the observed degradation of the system as a whole would still follow this pattern. The upshot of this is that a potentially useful life science model may have just materialized in artificial intelligence. The main flaw that I can see in it is that a cell is complex mechanism in and of itself, and so the success/failure of each might be subject to many factors in parallel as well. That is, it might not fail the way a short subroutine would were it copied badly, which is the gist of this. But then one might find a lower level where the parts were sufficiently monolithic that the analogy held. This seems to kick the butt of the good old 'Entropy' theory... cop-out. Incompentent nineteenth century philosophers leaned heavily on entropy. Comments? Flames? The name of a good shrink? Musing, Craig.
chiaraviglio@husc4.UUCP (06/07/87)
In article <622@unicus.UUCP> craig@unicus.UUCP (Craig D. Hubley) writes: >I've heard that mammal cells appear to suffer a "hard" reproductive limit >of 52 mitosis operations, and that meiosis "resets this counter" to 0. > >- any comment on this, bio-med types? Is it true? >- Would a theory assuming a simple variable or random "counter" in each cell >limiting its reproductive span better explain aging (programmed cells...) Random failure may be a significant factor in aging, but a hard limit on the number of times a cell may divide before it self-destructs has been observed in tissue culture, where the cells are for the most part not dependant on each other. Those cells which manage to get past the hard limit are abnormal (although not necessarily cancerous) in ways beyond their mere ability to keep dividing after they were supposed to self-destruct. I don't remember most of the details of this, but I do remember that they tend to become tetraploid (I think also aneuploid) due to an increase in the rate of mitotic failure. -- Lucius Chiaraviglio lucius%tardis@harvard.harvard.edu seismo!tardis.harvard.edu!lucius
davel@pixar.UUCP (David Longerbeam) (06/09/87)
In article <622@unicus.UUCP>, craig@unicus.UUCP (Craig D. Hubley) writes: > > This description of the human memory system, though cloaked in vaguer terms, > corresponds more or less one-to-one with the traditional computer > architecture we all know and love. To wit: [description deleted] > At least this far, this theory appears to owe a lot to computer science. > Granted, there is lots of empirical evidence in favour, but we all know > how a little evidence can go far too far towards developing an analogy. One of my philosophy professors in college offered the observation that models for the human mind have always seemed to correspond to the most advanced form of technology at that given point in history. He could recall that when he was young, this technology was the combustion engine, and lo, the cognitive psychologists' model at that time was the combustion engine. Of course, this technology is now the digital computer, and many psychologists, linguists and computer scientists use it as a model to explain activites of the human mind. Some go so far as to say that intelligence is nothing more than the result of following the same sorts of syntactical rules as performed by a computer! But I stray... I wanted to point out that you didn't give the source of the above model/ comparison, and that if it is not entirely empirical in nature, it may be a case of "use the latest technology as the best model". -- David Longerbeam || The opinions expressed above Pixar || are not to be contrued as the San Rafael, CA || opinions, stated or otherwise, ucbvax!pixar!davel (415) 499-3600 || of Pixar.
pell@boulder.UUCP (06/10/87)
(Craig D. Hubley) writes: (cognative psycology) >far from developing a bold new metaphor for human thinking, has (to a degree) >copied at least one metaphor from third-generation computer science. > one of the things that has always amused me is that, to the extent that I understand the structuring of computers, it seems that the cell and the computer scientists have come up with similar solutions to many of the same questions. This is particularly true when one looks at information flow in the cell. I feel comfortable in assuming that the cell had little help from the CS types in solving problems of information flow. It is likely to be true that contemporaries of in different scientific fields play with each other's ideas. This is why "Nature" insists on being so broad and why F.H.C.C. can get work. But I should stay more to the point. >The Question or WHAT DO YOU THINK? >---------------------------------- >Apparently, all human organ weights begin to decline shortly after puberty. >The cumulative effect of this seeming reduction of resources isn't felt so >strongly until middle-age, when we become more susceptible to disease. >- Is mitosis sufficiently prone to failure to account for organ decline? > >I've heard that mammal cells appear to suffer a "hard" reproductive limit >of 52 mitosis operations, and that meiosis "resets this counter" to 0. > It would seem to me that the step that is likely to give the cell trouble is not mitosis but DNA replication. If a whole chromosome lost or non-disjoined, that cell is in some serious trouble. Progressive accumulation mistakes through replication and general maintanence seems a more likely culprit. I confess that once the topic turns to outside the single cell or involves more than, say, two cells, I am hopelssly lost. So the question of aging is outside my capabilities. This will not, of course, stop me from volenteering the following: I have never liked the "hard-wired-number-of-mitosis" model. I am not sure why; it just seems implausible, or worse yet, unecessary. Supposedly "immortal" cells, like bacteria, actually have a rather high death rate in the population (try doing a particle count then plating them out to see how many are actually able to continue dividing). Their apparent immortality is the result of unrestrained growth. I suspect the failure rate is similar between bacteria and individual cells of a metazoan. The difference may be simply that a metazoan cannot tolerate unrestrained growth of cell populations. The cells are forced to stop dividing when in contact with other cells. they can be induced to re-enter the cycle by growth factors released, for example, when the skin is cut. I would guess that if one coupled the limitations on growth necessary to be a metazoan with accumulated errors, both during replication and simple maitanence, one could explain gradual breakdown of tissue without invoking the "hard-wire" model. oh well, I've gone on too long already. tony (few degrees are worth remembering--and none are worth predicting) Pelletier Molecular etc. Bio Boulder, Co. 80309-0347 P.S. I think alot about information flow problems and would enjoy discussions on that...if anyone wants to chat.
todd@uhccux.UUCP (06/10/87)
In article <836@pixar.UUCP> davel@pixar.UUCP (David Longerbeam) writes: >In article <622@unicus.UUCP>, craig@unicus.UUCP (Craig D. Hubley) writes: >> This description of the human memory system, though cloaked in vaguer terms, >> corresponds more or less one-to-one with the traditional computer >> architecture we all know and love. To wit: > [description deleted] >> At least this far, this theory appears to owe a lot to computer science. >> Granted, there is lots of empirical evidence in favour, but we all know >> how a little evidence can go far too far towards developing an analogy. >One of my philosophy professors in college offered the observation that >models for the human mind have always seemed to correspond to the most >advanced form of technology at that given point in history. He could It's true that theories of cognition often reflect the current popular technology. But before we start arguing current theories as reflections of computer science and physiology, I suggest we at least have some common starting point for our discussion. I don't want to suggest that you need a Ph.D. in Cognitive Psychology to discuss the subject, but you might want to consider reading one of the many intro texts on the subject before leaping to any speculations (wild or otherwise :-). An intro text I often recommend to people with a more than casual interest in cognition is: Anderson, John (1985). Cognitive Psychology and Its Implications. (2nd edition) New York: W.H. Freeman and Co. If you are interested in a historical perspective of psychological research, I suggest you take a peek at: Hearst, Eliot (Ed.) (1979). The First Century of Experimental Psychology. Hillsdale, New Jersey: Lawrence Erlbaum Associates, Pub. And finally, though I don't always agree with what Richard Gregory has to say, I always enjoy hearing or reading his ideas and theories. His "Mind in Science" is an interesting speculative book. Gregory, Richard (1981). Mind in Science: A History of Explanations in Psychology and Physics. Cambridge: Cambridge University Press Well, I hope we at least have some common reference point now... Todd Ogasawara "With a good wind behind me and and a lot of luck... Ph.D. in Psychology later this year :-)" -- Todd Ogasawara, U. of Hawaii Computing Center UUCP: {ihnp4,seismo,ucbvax,dcdwest}!sdcsvax!nosc!uhccux!todd ARPA: uhccux!todd@nosc.MIL INTERNET: todd@uhccux.UHCC.HAWAII.EDU
bchso@uhnix2.UUCP (06/11/87)
In article <1331@sigi.Colorado.EDU> pell@boulder.Colorado.EDU (Anthony Pelletier) writes: >P.S. I think alot about information flow problems and would enjoy >discussions on that...if anyone wants to chat. Do you know about the "Matrix of Biological Knowledge Workshop" in Santa Fe, NM July 13-August 14 this year? One of the subjects is "information flow from DNA to cells" lead by Dickerson of UCLA, Hershman, also UCLA, and Smith from MBCRR at Harvard. For information, contact Ms. Ginger Richardson at The Santa Fe Institute, P.O. Box 9020, Santa Fe, N.M. 87504-9020; phone 505-984-8800. dr. dan davison/ Dept of Biochemical and Biophysical Sciences/ U. of Houston bitnet: bchs6\@uhupvm1.bitnet | 4800 Calhoun/ Houston, Tx 77004 arpanet: davison\@sumex-aim.stanford.edu|uucp:...rice!academ!uhnix1!uhnix2!bchso
lambert@mcvax.UUCP (06/14/87)
In article <836@pixar.UUCP> davel@pixar.UUCP (David Longerbeam) writes: > In article <622@unicus.UUCP>, craig@unicus.UUCP (Craig D. Hubley) writes: | | > This description of the human memory system, though cloaked in vaguer terms, | > corresponds more or less one-to-one with the traditional computer | > architecture we all know and love. To wit: | | [description deleted] | | > At least this far, this theory appears to owe a lot to computer science. | > Granted, there is lots of empirical evidence in favour, but we all know | > how a little evidence can go far too far towards developing an analogy. | | One of my philosophy professors in college offered the observation that | models for the human mind have always seemed to correspond to the most > advanced form of technology at that given point in history. I find the connection between models of human memory as developed in cognitive psychology and existing computer architectures rather tenuous. The main similarity appears to be that several levels of memory can be discerned, but the suggested analogy in function is a bit far-fetched. It is perhaps worth pointing out that much of the current models in cognitive psychology can already be found in the pioneering work of Otto Selz (Muenchen, 1881 - Auschwitz, 1943), antedating the computer era. -- Lambert Meertens, CWI, Amsterdam; lambert@cwi.nl
tjhorton@utai.UUCP (06/15/87)
>lambert@cwi.nl (Lambert Meertens) writes: >It is perhaps worth pointing out that much of the current models in >cognitive psychology can already be found in the pioneering work of Otto >Selz (Muenchen, 1881 - Auschwitz, 1943), antedating the computer era. 1943 was at least 7 years after Turing published his paper (fifty years ago, last November) and 5 years after Shannon published his thesis about information theory. Although I don't know Selz, his life definitely spanned into the dawn of the "computer era". It's interesting - do these models of his pre-date these "computeresque" notions? Timothy J Horton <tjhorton@utai.toronto.edu>
diaz@aecom.YU.EDU (Dizzy Dan) (06/16/87)
In article <395@uhnix2.UUCP>, bchso@uhnix2.UUCP (Dan Davison) writes: > Do you know about the "Matrix of Biological Knowledge Workshop" in Santa Fe, > NM > July 13-August 14 this year? One of the subjects is "information flow from > DNA to cells" lead by Dickerson of UCLA, Hershman, also UCLA, and Smith from > MBCRR at Harvard. > > For information, contact Ms. Ginger Richardson at The Santa Fe Institute, > P.O. Box 9020, Santa Fe, N.M. 87504-9020; phone 505-984-8800. > Sorry gang, but applications for the Matrix Workshop were due in April. If you are interested, the Santa Fe Institute may be able to put you in touch with some of the faculty running the workshops. -- 5'gtacggagc dn/dx = Dan Diaz (philabs!aecom!diaz) Department of Molecular Biology & Snake Oil Dynamics Albert Slimestein College of Medicine ctataacagcta 3'