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<DIV><FONT face=Arial color=#0000ff size=2><SPAN class=734124719-04092008>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><SPAN
style="FONT-SIZE: 10pt; COLOR: blue; FONT-FAMILY: Arial">Perhaps Eugene can
respond to some of the questions here. I am sure he understands and can relate
to some of the ideas in artificial neural networks. And we of course learn
all the time from new discoveries in biology and neuroscience.</SPAN><SPAN
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<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><SPAN
style="FONT-SIZE: 10pt; COLOR: blue; FONT-FAMILY: Arial">I believe the sense of
the argument here is that learning is simply some "fine tuning" of some existing
structures. Adult neurogenesis shows that new networks can be created and put
into operation. And that's not some simple "fine tuning." And I believe there is
plenty of evidence to show that there is remodeling and reconfiguration in the
brain (new connections, synaptic adjustments). Perhaps someone can help out with
some references. I don't have anything handy.</SPAN><o:p></o:p></P>
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<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><FONT><FONT
face="Times New Roman" color=#000000 size=3><o:p><SPAN
class=734124719-04092008>Asim</SPAN></o:p></FONT></FONT></P>
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face="Times New Roman" color=#000000 size=3><o:p><SPAN
class=734124719-04092008></SPAN></o:p></FONT></FONT> </P>
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face="Times New Roman" color=#000000 size=3><o:p><SPAN
class=734124719-04092008></SPAN></o:p></FONT></FONT> </P></SPAN></FONT><FONT
face=Tahoma size=2>-----Original Message-----<BR><B>From:</B>
comp-neuro-bounces@neuroinf.org [mailto:comp-neuro-bounces@neuroinf.org]<B>On
Behalf Of </B>Mario Negrello<BR><B>Sent:</B> Thursday, September 04, 2008 2:17
AM<BR><B>To:</B> CompNeuro List<BR><B>Subject:</B> [Comp-neuro]
Development,Evolution and Learning (was) Discussion - Kuhn - and brief
comments<BR><BR></FONT></DIV>
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<DIV dir=ltr><FONT class=Apple-style-span color=#000000><FONT
class=Apple-style-span color=#144fae><BR></FONT>Asim
said:</FONT> </DIV>
<DIV dir=ltr><SPAN class=531280007-01092008><FONT color=#0000ff>On the
"blank slate" idea in ANN, just look at the phenomenon of adult
neurogenesis. Our adult brains generate new cells in the thousands on a
daily basis and they are part of the "blank slate" because they don't come
with ready-made connections or anything. The process that you refer to as
"<FONT color=#000000>development probably recapitulating evolutionary
history" </FONT></FONT><FONT color=#0000ff>is called "learning" in ANN. It's
that process that constructs networks out of these new cells and makes
them operational.</FONT></SPAN></DIV></DIV></BLOCKQUOTE>
<DIV><BR></DIV>
<DIV>I guess that this varies with your level of analysis. Developmental
recapitulation of evolutionary history is about major brain development, hubs
and tracts and gross architecture, those features that are morphologically
conspicuous in the brain. Learning is different, it's fine tuning, when an
already functional brain develops further functionality by interacting with a
complex environment. Moreover, as was pointed out by Cottrell, the new neurons
you mention do not sprout anywhere, but presumably, noly where there is a
reason or a function for them to do. One of the stories i know about new
neurons being generated relates to communication behavior in fish. Fish that
produce aggressive calls, grow new cells to make their calls more potent. This
was solidly shown in:</DIV>
<DIV><BR></DIV>
<DIV>Dunlap, K.D., et al 2006. Social interaction and cortisol treatment
increase cell addition and radial glia fiber density in the diencephalic
periventricular zone of adult electric fish, Apteronotus leptorhynchus,
Hormones & Behavior 50:10-17.</DIV>
<DIV><BR></DIV>
<DIV>So, between cell addition and brain development there is a considerable
distance. I do not suppose that by explaining mechanisms of learning, we shall
also understand the functional entailments of particular
architectures. </DIV>
<DIV><BR></DIV>
<DIV>For instance, Eugene Izhikevich in a talk in 'Dynamical Systems in
Neuroscience' at the NYU in June 2008 (if memory serves me right), showed the
last output of his mega brain model. The model has the gross architecture of a
human brain as seen through DTI (diffusion tensor imaging), and the
microarchitecture derived from rats and cats. What surprised me in terms of
the results, was that he claimed that frequencies measured from the model
resembled those known from their correspodent areas of the brain. Alpha in V1,
Theta in hippocampus, and others.</DIV>
<DIV>I take that to mean that many functional capabilities of the brain will
be effectively only learneable if the proper architecture is there. Else, if
it were only learning, there would be little reason for a cat to be unable to
learn the things a human does. </DIV>
<DIV><BR></DIV>
<DIV>Surely, one can draw analogies from evolution, through development, until
learning. One can amalgamate all and say that they are all 'metastable
adaptations', or something. But so far, the clear divisions that appear
between the study of each, are fully justified: we need theories for
each. For all, later. Learning needs its story as much as
development. </DIV>
<DIV><BR></DIV>Gruss,</DIV>
<DIV><BR></DIV>
<DIV>M.<BR>
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<DIV class=OutlookMessageHeader dir=ltr align=left><FONT face=Tahoma
size=2>-----Original Message-----<BR><B>From:</B> <A
href="mailto:comp-neuro-bounces@neuroinf.org">comp-neuro-bounces@neuroinf.org</A>
[<A
href="mailto:comp-neuro-bounces@neuroinf.org">mailto:comp-neuro-bounces@neuroinf.org</A>]<B>On
Behalf Of </B>james bower<BR><B>Sent:</B> Wednesday, August 27, 2008
9:05 AM<BR><B>To:</B> CompNeuro List<BR><B>Subject:</B> [Comp-neuro]
Discussion - Kuhn - and brief comments<BR><BR></FONT></DIV>
<DIV>A few brief comments -- given that school has started, and I now
have to prepare to "influence" the latest next generation.</DIV>
<DIV><BR></DIV>
<DIV>First a BIG POINT:</DIV>
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<DIV>
<DIV>
<DIV><BR></DIV>
<DIV>Klaus Stiefel: pre-paradigmatic " What he meant by that
is a disagreement about the basic explainanda"</DIV>
<DIV><BR></DIV>
<DIV>No, Kuhn was focused on process to quote: "the early
developmental stages of most sciences (are) characterized by continual
competition between a number of distinct views of nature, each partially
derived from, and all roughly compatible with, the dictates of
scientific observation and method, (In pre-paradigmatic science)
what differentiates these various schools (is) not one or another
failure of method - they are all "scientific" - but what we shall come
to call their incommensurable ways of seeing the world and practicing
science within it" (pg 4 The Structure of Scientific Revolution.)
If this discussion over the last two months doesn't make it clear
that, as a field, we currently have "incommensurate ways of seeing the
world and practicing science within it" I don't know what does.
Kuhn goes on to say: "Men (sic) whose research is based on
shared paradigms are committed to the same rules and standards for
scientific practice." Again, this discussion makes it pretty clear
to me that we have not yet reached that point. In fact, (and I
would say reflecting this fact) the kind of discussion we have been
having here seldom ever happens as we are content (and being
pre-paradigmatic can get away with) agreeing to not discuss what we
don't agree on, another characteristic of pre-paradigmatic science --
and the reason I don't mind starting these discussions.</DIV>
<DIV><BR></DIV>
<DIV>Bryan Bishop: "There's a few too many layers of folk
psychology here,"</DIV>
<DIV><BR></DIV>
<DIV>I agree, and have characterized all of biology as fundamentally
folkloric in nature -- based on story telling, with few real definitions
of anything. Something comp bio (neuro) will, I hope, eventually
fix.</DIV>
<DIV><BR></DIV>
<DIV><BR></DIV>
<DIV><BR></DIV>
<DIV>And on to the approaches we don't agree on:</DIV>
<DIV><BR></DIV>
<DIV><SPAN class=Apple-style-span
style="TEXT-DECORATION: underline">Bryan Bishop</SPAN>: "I bet it
becomes clear that trying to do "natural language processing" from
statistical inferences doesn't get us as much hard science as the brain
could provide."</DIV>
<DIV><BR></DIV>
<DIV>Of course, I agree -- and also agree that this field continues to
be distorted by what is essential snake oil we sell to the Department of
Defense about how studying the brain will help win wars. This
rather self serving commitment to "neuro-morphic engineering" as it is
now called, has been distorting our science for a while. In the
last 8 years even more dramatically. </DIV>
<DIV><BR></DIV>
<DIV>Mario Negrello: "I'd say instead that some approaches gather
more acolytes, and then overflow others in sheer voluminous
quantity,"</DIV>
<DIV><BR></DIV>
<DIV>Unfortunately, as just noted, very often related to who you are
selling the science to (funders) and also, unfortunately, how 'easy' the
methods are and therefore how many can jump on the bandwagon without
much preparation (or even knowledge of the brain in this case) --
20 years studying the realistic model of the Purkinje cell and counting.
</DIV>
<DIV><BR></DIV>
<DIV>
<DIV><BR></DIV>
<DIV>Bard Ermentrout: " I suspect that it would be too hard
to adjust parameters for realistic models "</DIV>
<DIV><BR></DIV>
<DIV>Is hard bad? Or is the brain, in fact, hard?</DIV>
<DIV><BR></DIV></DIV>
<DIV><BR>
<DIV apple-content-edited="true">
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<DIV>
<DIV>
<DIV><SPAN class=Apple-style-span
style="TEXT-DECORATION: underline; -webkit-text-decorations-in-effect: underline">Igor
Carron</SPAN>: "The groundwork of theory as you put it has,
in nuclear technology, always been a way to acquire and use
experimental findings."
<DIV><BR></DIV>And this, in fact, is the value of theory -- not to
capture 'truth' as many in comp neuro seem be believe, but to organize
experimental studies -- the more the theory is removed from the actual
structure of the brain - the more it exists by itself, disconnected from
the ability to improve, or more importantly to refute it.</DIV>
<DIV><BR></DIV>
<DIV><BR></DIV>
<DIV><SPAN class=Apple-style-span
style="TEXT-DECORATION: underline; -webkit-text-decorations-in-effect: underline">Asim
Roy</SPAN>: "a "blank slate" simply implies a network whose
connection weights and other parameters have not been set yet -"</DIV>
<DIV><BR></DIV>
<DIV>And, no such thing in biology, where development doesn't end and
learning begins - it is continuous, and development probably
recapitulating evolutionary history. Another reason why the
mainstream ANN models make no sense.</DIV>
<DIV><BR></DIV>
<DIV><BR></DIV>
<DIV>Asim Roy: "Is there a way in computational neuroscience to verify
any of these theories of learning? "</DIV>
<DIV><BR></DIV>
<DIV>Wrong question.</DIV>
<DIV><BR></DIV>
<DIV><BR></DIV>
<DIV>Axel Hutt: " can (neuro)biology really treat
a population of some thousand elements ? "</DIV>
<DIV><BR></DIV>
<DIV>We will need to figure out how - numerous groups are working on
it.</DIV>
<DIV><BR></DIV>
<DIV><BR></DIV>
<DIV>Anibalmastobiza: "cerebellum, usually considered as a center
for motor processing and coordination just as it was for the
basal ganglia that now we know that is also involve in cognition"</DIV>
<DIV><BR></DIV>
<DIV>While I appreciate the support, I have another question for
cognitive neuroscientists, how come anything that lights up in a brain
scan becomes a "cognitive center" seems weird to me. </DIV>
<DIV><BR></DIV>
<DIV><BR></DIV>
<DIV>Jim</DIV>
<DIV><BR></DIV>
<DIV><BR></DIV>
<DIV><BR></DIV>
<DIV><BR></DIV>
<DIV><BR></DIV></DIV></DIV></DIV></DIV></DIV>
<DIV><BR><BR class=webkit-block-placeholder></DIV>
<DIV><BR class=webkit-block-placeholder></DIV>
<DIV>==================================</DIV>
<DIV><BR class=webkit-block-placeholder></DIV>
<DIV>Dr. James M. Bower Ph.D.</DIV>
<DIV><BR></DIV>
<DIV>Professor of Computational Neuroscience</DIV>
<DIV><BR></DIV>
<DIV>Research Imaging Center</DIV>
<DIV>University of Texas Health Science Center - </DIV>
<DIV>- San Antonio</DIV>
<DIV>8403 Floyd Curl Drive</DIV>
<DIV>San Antonio Texas 78284-6240</DIV>
<DIV><BR></DIV>
<DIV>Main Number: 210- 567-8100</DIV>
<DIV>Fax: 210 567-8152</DIV>Mobile: 210-382-0553
<DIV><BR>
<DIV>
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