<html><head></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><font class="Apple-style-span" face="Arial" size="4">Dear Tsvi,</font><div><font class="Apple-style-span" face="Arial" size="4"><br></font></div><div><font class="Apple-style-span" face="Arial" size="4">You mention Adaptive Resonance below and suggest that it "requires complex signals indicating when to stop, compare, and cycle". That is not correct. </font></div><div><font class="Apple-style-span" face="Arial" size="4"><br></font></div><div><font class="Apple-style-span" face="Arial" size="4">ART uses a simple measure of pattern mismatch. Moreover, psychological, neurophysiological, anatomical, and ERP data support the operations that it models during hypothesis testing and memory search. ART predicted various of these data before they were collected.</font></div><div><font class="Apple-style-span" face="Arial" size="4"><br></font></div><div><font class="Apple-style-span" face="Arial" size="4">If you would like to pursue this further, see <a href="http://cns.bu.edu/~steve/ART.pdf">http://cns.bu.edu/~steve/ART.pdf</a> for a recent heuristic review.</font></div><div><font class="Apple-style-span" face="Arial" size="4"><br></font></div><div><font class="Apple-style-span" face="Arial" size="4">Best,</font></div><div><font class="Apple-style-span" face="Arial" size="4"><br></font></div><div><font class="Apple-style-span" face="Arial" size="4">Steve</font></div><div><font class="Apple-style-span" face="Arial" size="4"><br></font></div><div><font class="Apple-style-span" face="Arial" size="4"><br></font><div><div><font class="Apple-style-span" face="Arial" size="4">On Mar 21, 2014, at 10:29 PM, Tsvi Achler wrote:</font></div><font class="Apple-style-span" face="Arial" size="4"><br class="Apple-interchange-newline"></font><blockquote type="cite"><div><font class="Apple-style-span" face="Arial" size="4">Sorry for the length of this response but I wanted to go into some<br>detail here.<br><br>I see the habituation paradigm as somewhat analogous to surprise and<br>measurement of error during recognition. I can think of a few<br>mathematical Neural Network classifiers that can generate an internal<br>pattern for match during recognition to calculate this<br>habituation/surprise orientation. Feedforward networks definitely<br>will not work because they don't recall the internal stimulus very<br>well. One option is adaptive resonance (which I assume you use), but<br>it cycles through the patterns one at a time and requires complex<br>signals indicating when to stop, compare, and cycle. I assume<br>Juyang's DN can also do something similar but I suspect it also must<br>cycle since it also has lateral inhibition. Bidirectional Associative<br>Memories (BAM) may also be used. Others such as Bayes networks and<br>free-energy principle can used, although they are not as easily<br>translatable to neural networks.<br><br>Another option is a network like mine which does not have lateral<br>connections but also generates internal patterns. The advantage is<br>that it can also generate mixtures of patterns at once, does not cycle<br>through individual patterns, does not require signals associated with<br>cycling, and can be shown mathematically to be analogous to<br>feedforward networks. The error signal it produces can be used for an<br>orientation reflex or what I rather call attention. It is essential<br>for recognition and planning.<br><br>I would be happy to give a talk on this and collaborate on a rigorous<br>comparison. Indeed it is important to look at models other than those<br>using feedforward connections during recognition.<br><br>Sincerely,<br><br>-Tsvi<br><br><br><br><br>On Mar 21, 2014 5:25 AM, "Kelley, Troy D CIV (US)"<br><<a href="mailto:troy.d.kelley6.civ@mail.mil">troy.d.kelley6.civ@mail.mil</a>> wrote:<br></font><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Classification: UNCLASSIFIED<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Caveats: NONE<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Yes, Mark, I would argue that habituation is anticipatory prediction. The<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">neuron creates a model of the incoming stimulus and the neuron is<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">essentially predicting that the next stimuli will be comparatively similar<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">to the previous stimulus. If this prediction is met, the neuron habituates.<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">That is a simple, low level, predictive model.<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">-----Original Message-----<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">From: Mark H. Bickhard [mailto:mhb0@Lehigh.EDU]<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Sent: Thursday, March 20, 2014 5:28 PM<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">To: Kelley, Troy D CIV (US)<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Cc: Tsvi Achler; Andras Lorincz; <a href="mailto:bower@uthscsa.edu">bower@uthscsa.edu</a>;<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><a href="mailto:connectionists@mailman.srv.cs.cmu.edu">connectionists@mailman.srv.cs.cmu.edu</a><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Subject: Re: Connectionists: how the brain works?<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">I would agree with the importance of Sokolov habituation, but there is more<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">than one way to understand and generalize from this phenomenon:<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><a href="http://www.lehigh.edu/~mhb0/AnticipatoryBrain20Aug13.pdf">http://www.lehigh.edu/~mhb0/AnticipatoryBrain20Aug13.pdf</a><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Mark H. Bickhard<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Lehigh University<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">17 Memorial Drive East<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Bethlehem, PA 18015<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><a href="mailto:mark@bickhard.name">mark@bickhard.name</a><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><a href="http://bickhard.ws/">http://bickhard.ws/</a><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">On Mar 20, 2014, at 4:41 PM, Kelley, Troy D CIV (US) wrote:<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">We have found that the habituation algorithm that Sokolov discovered way<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">back in 1963 provides an useful place to start if one is trying to determine<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">how the brain works. The algorithm, at the cellular level, is capable of<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">determining novelty and generating implicit predictions - which it then<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">habituates to. Additionally, it is capable of regenerating the original<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">response when re-exposed to the same stimuli. All of these behaviors<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">provide an excellent framework at the cellular level for explain all sorts<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">of high level behaviors at the functional level. And it fits the Ockham's<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">razor principle of using a single algorithm to explain a wide variety of<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">explicit behavior.<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Troy D. Kelley<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">RDRL-HRS-E<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Cognitive Robotics and Modeling Team Leader Human Research and Engineering<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Directorate U.S. Army Research Laboratory Aberdeen, MD 21005 Phone<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">410-278-5869 or 410-278-6748 Note my new email address:<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><a href="mailto:troy.d.kelley6.civ@mail.mil">troy.d.kelley6.civ@mail.mil</a><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">On 3/20/14 10:41 AM, "Tsvi Achler" <<a href="mailto:achler@gmail.com">achler@gmail.com</a>> wrote:<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">I think an Ockham's razor principle can be used to find the most<br></font></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">optimal algorithm if it is interpreted to mean the model with the<br></font></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">least amount of free parameters that captures the most phenomena.<br></font></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><a href="http://reason.cs.uiuc.edu/tsvi/Evaluating_Flexibility_of_Recognition.p">http://reason.cs.uiuc.edu/tsvi/Evaluating_Flexibility_of_Recognition.p</a><br></font></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">df<br></font></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">-Tsvi<br></font></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">On Wed, Mar 19, 2014 at 10:37 PM, Andras Lorincz <<a href="mailto:lorincz@inf.elte.hu">lorincz@inf.elte.hu</a>><br></font></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">wrote:<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Ockham works here via compressing both the algorithm and the structure.<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Compressing the structure to stem cells means that the algorithm<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">should describe the development, the working, and the time dependent<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">structure of the brain. Not compressing the description of the<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">structure of the evolved brain is a different problem since it saves<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">the need for the description of the development, but the working.<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Understanding the structure and the working of one part of the brain<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">requires the description of its communication that increases the<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">complexity of the description. By the way, this holds for the whole<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">brain, so we might have to include the body at least; a structural<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">minimist may wish to start from the genetic code, use that hint and<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">unfold the already compressed description. There are (many and<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">different) todos 'outside' ...<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Andras<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">.<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">________________________________<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">From: Connectionists <<a href="mailto:connectionists-bounces@mailman.srv.cs.cmu.edu">connectionists-bounces@mailman.srv.cs.cmu.edu</a>><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">on behalf of james bower <<a href="mailto:bower@uthscsa.edu">bower@uthscsa.edu</a>><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Sent: Thursday, March 20, 2014 3:33 AM<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">To: Geoffrey Goodhill<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Cc: <a href="mailto:connectionists@mailman.srv.cs.cmu.edu">connectionists@mailman.srv.cs.cmu.edu</a><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Subject: Re: Connectionists: how the brain works?<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Geoffrey,<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Nice addition to the discussion actually introducing an interesting<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">angle on the question of brain organization (see below) As you note,<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">reaction diffusion mechanisms and modeling have been quite successful<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">in replicating patterns seen in biology - especially interesting I<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">think is the modeling of patterns in slime molds, but also for very<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">general pattern formation in embryology. However, more and more<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">detailed analysis of what is diffusing, what is sensing what is<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">diffusing, and what is reacting to substances once sensed -- all<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">linked to complex patterns of gene regulation and expression have<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">made it clear that actual embryological development is much much more<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">complex, as Turing himself clearly anticipated, as the quote you cite pretty<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">clearly indicates. Clearly a smart guy. But, I don't actually think<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">that<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">this is an application of Ochham's razor although it might appear to<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">be after the fact. Just as Hodgkin and Huxley were not applying it<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">either in<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">their model of the action potential. Turing apparently guessed (based<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">on a<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">lot of work at the time on pattern formation with reaction diffusion)<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">that such a mechanism might provide the natural basis for what<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">embryos do. Thus, just like for Hodgkin and Huxley, his model<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">resulted from a bio-physical insight, not an explicit attempt to<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">build a stripped down model for its own sake. I seriously doubt<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">that Turning would have claimed that he, or his models could more<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">effectively do what biology actually does in forming an embrio, or<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">substitute for the actual process.<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">However, I think there is another interesting connection here to the<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">discussion on modeling the brain. Almost certainly communication and<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">organizational systems in early living beings were reaction diffusion<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">based.<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">This is still a dominant effect for many 'sensing' in small organisms.<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Perhaps, therefore, one can look at nervous systems as structures<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">specifically developed to supersede reaction diffusion mechanisms,<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">thus superseding this very 'natural' but complexity limited type of<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">communication and organization. What this means, I believe, is that<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">a simplified or abstracted physical or mathematical model of the<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">brain explicitly violates the evolutionary pressures responsible for<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">its structure. Its where the wires go, what the wires do, and what<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">the receiving neuron does with the information that forms the basis<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">for neural computation, multiplied by a very large number. And that<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">is dependent on the actual physical structure of those elements.<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">One more point about smart guys, as a young computational<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">neurobiologist I questioned how insightful John von Neumann actually<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">was because I was constantly hearing about a lecture he wrote (but<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">didn't give) at Yale suggesting that dendrites and neurons might be<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">digital ( John von Neumann's The Computer and the Brain. (New<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Haven/London: Yale Univesity Press, 1958.) Very clearly a not very<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">insightful idea for a supposedly smart guy. It wasn't until a few<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">years later, when I actually read the lecture - that I found out that<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">he ends by stating that this idea is almost certainly wrong, given<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">the likely nonlinearities in neuronal dendrites. So von Neumann<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">didn't lack insight, the people who quoted him did. It is a<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">remarkable fact that more than 60 years later, the majority of models of<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">so called neurons built by engineers AND neurobiologists don't consider<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">these nonlinearities.<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">The point being the same point, to the Hopfield, Mead, Feynman list,<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">we can now add Turing and von Neumann as suspecting that for<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">understanding, biology and the nervous system must be dealt with in their<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">full complexity.<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">But thanks for the example from Turing - always nice to consider actual<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">examples. :-)<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Jim<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">On Mar 19, 2014, at 8:30 PM, Geoffrey Goodhill <<a href="mailto:g.goodhill@uq.edu.au">g.goodhill@uq.edu.au</a>><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">wrote:<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Hi All,<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">A great example of successful Ockham-inspired biology is Alan<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Turing's model for pattern formation (spots, stripes etc) in<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">embryology (The chemical basis of morphogenesis, Phil Trans Roy Soc,<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">1953). Turing introduced a physical mechanism for how inhomogeneous<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">spatial patterns can arise in a biological system from a spatially<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">homogeneous starting point, based on the diffusion of morphogens. The<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">paper begins:<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">"In this section a mathematical model of the growing embryo will be<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">described. This model will be a simplification and an idealization,<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">and consequently a falsification. It is to be hoped that the features<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">retained for discussion are those of greatest importance in the<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">present state of knowledge."<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">The paper remained virtually uncited for its first 20 years following<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">publication, but since then has amassed 8000 citations (Google<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Scholar). The subsequent discovery of huge quantities of molecular<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">detail in biological pattern formation have only reinforced the<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">importance of this relatively simple model, not because it explains<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">every system, but because the overarching concepts it introduced have<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">proved to be so fertile.<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Cheers,<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Geoff<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">On Mar 20, 2014, at 6:27 AM, Michael Arbib wrote:<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Ignoring the gross differences in circuitry between hippocampus and<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">cerebellum, etc., is not erring on the side of simplicity, it is<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">erring, period. Have you actually looked at a<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Cajal/Sxentagothai-style drawing of their circuitry?<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">At 01:07 PM 3/19/2014, Brian J Mingus wrote:<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Hi Jim,<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Focusing too much on the details is risky in and of itself. Optimal<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">compression requires a balance, and we can't compute what that<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">balance is (all models are wrong). One thing we can say for sure is<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">that we should err on the side of simplicity, and adding detail to<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">theories before simpler explanations have failed is not Ockham's<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">heuristic. That said it's still in the space of a Big Data fuzzy<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">science approach, where we throw as much data from as many levels of<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">analysis as we can come up with into a big pot and then construct a<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">theory. The thing to keep in mind is that when we start pruning this<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">model most of the details are going to disappear, because almost all<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">of them are irrelevant. Indeed, the size of the description that<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">includes all the details is almost infinite, whereas the length of<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">the description that explains almost all the variance is extremely<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">short, especially in comparison. This is why Ockham's razor is a good<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">heuristic. It helps prevent us from wasting time on unnecessary<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">details by suggesting that we only inquire as to the details once our<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">existing simpler theory has failed to work.<br></font></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">On 3/14/14 3:40 PM, Michael Arbib wrote:<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">At 11:17 AM 3/14/2014, Juyang Weng wrote:<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">The brain uses a single architecture to do all brain functions we are<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">aware of! It uses the same architecture to do vision, audition,<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">motor, reasoning, decision making, motivation (including pain<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">avoidance and pleasure seeking, novelty seeking, higher emotion, etc.).<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Gosh -- and I thought cerebral cortex, hippocampus and cerebellum<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">were very different from each other.<br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></blockquote></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Troy D. Kelley<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">RDRL-HRS-E<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Cognitive Robotics and Modeling Team Leader Human Research and Engineering<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Directorate U.S. Army Research Laboratory Aberdeen, MD 21005 Phone<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">410-278-5869 or 410-278-6748 Note my new email address:<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><a href="mailto:troy.d.kelley6.civ@mail.mil">troy.d.kelley6.civ@mail.mil</a><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Classification: UNCLASSIFIED<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4">Caveats: NONE<br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote><blockquote type="cite"><font class="Apple-style-span" face="Arial" size="4"><br></font></blockquote></div></blockquote></div><font class="Apple-style-span" face="Arial" size="4"><br></font><div>
<font class="Apple-style-span" face="Arial" size="4"><span class="Apple-style-span" style="border-collapse: separate; color: rgb(0, 0, 0); font-variant: normal; letter-spacing: normal; line-height: normal; orphans: 2; text-align: -webkit-auto; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-border-horizontal-spacing: 0px; -webkit-border-vertical-spacing: 0px; -webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; "><span class="Apple-style-span" style="border-collapse: separate; color: rgb(0, 0, 0); font-variant: normal; letter-spacing: normal; line-height: normal; orphans: 2; text-align: -webkit-auto; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-border-horizontal-spacing: 0px; -webkit-border-vertical-spacing: 0px; -webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; "><div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><span class="Apple-style-span" style="border-collapse: separate; color: rgb(0, 0, 0); font-variant: normal; letter-spacing: normal; line-height: normal; orphans: 2; text-align: -webkit-auto; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-border-horizontal-spacing: 0px; -webkit-border-vertical-spacing: 0px; -webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px; "><div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><div><div><div><div>Stephen Grossberg</div><div>Wang Professor of Cognitive and Neural Systems</div><div>Professor of Mathematics, Psychology, and Biomedical Engineering</div><div><div>Director, Center for Adaptive Systems <a href="http://www.cns.bu.edu/about/cas.html">http://www.cns.bu.edu/about/cas.html</a></div></div><div><a href="http://cns.bu.edu/~steve">http://cns.bu.edu/~steve</a></div><div><a href="mailto:steve@bu.edu">steve@bu.edu</a></div></div></div></div><div><br></div></div></span></div></span><br class="Apple-interchange-newline"></span><br class="Apple-interchange-newline">
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