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[…] Analogy is the core of all thinking. – This is the simple but unorthodox premise that Pulitzer Prize-winning author Douglas Hofstadter and French psychologist Emmanuel Sander defend in their new work. Hofstadter has been grappling with the mysteries of human thought for over thirty years. Now, with his trademark wit and special talent for making complex ideas vivid, he has partnered with Sander to put forth a highly novel perspective on cognition. We are constantly faced with a swirling and intermingling multitude of ill-defined situations. Our brain’s job is to try to make sense of this unpredictable, swarming chaos of stimuli. How does it do so? The ceaseless hail of input triggers analogies galore, helping us to pinpoint the essence of what is going on. Often this means the spontaneous evocation of words, sometimes idioms, sometimes the triggering of nameless, long-buried memories.
Why did two-year-old Camille proudly exclaim, “I undressed the banana!”? Why do people who hear a story often blurt out, “Exactly the same thing happened to me!” when it was a completely different event? How do we recognize an aggressive driver from a split-second glance in our rear-view mirror? What in a friend’s remark triggers the offhand reply, “That’s just sour grapes”? What did Albert Einstein see that made him suspect that light consists of particles when a century of research had driven the final nail in the coffin of that long-dead idea? The answer to all these questions, of course, is analogy-making – the meat and potatoes, the heart and soul, the fuel and fire, the gist and the crux, the lifeblood and the wellsprings of thought. Analogy-making, far from happening at rare intervals, occurs at all moments, defining thinking from top to toe, from the tiniest and most fleeting thoughts to the most creative scientific insights.
Like Gödel, Escher, Bach before it, Surfaces and Essences will profoundly enrich our understanding of our own minds. By plunging the reader into an extraordinary variety of colorful situations involving language, thought, and memory, by revealing bit by bit the constantly churning cognitive mechanisms normally completely hidden from view, and by discovering in them one central, invariant core – the incessant, unconscious quest for strong analogical links to past experiences – this book puts forth a radical and deeply surprising new vision of the act of thinking. […] intro to “Surfaces and Essences – Analogy as the fuel and fire of thinking” by Douglas Hofstadter and Emmanuel Sander, Basic Books, NY, 2013 [link] (to be released May 1, 2013).
Picture – The idea of Viera da Silva’s art as a kind of code to be decoded comes across most clearly in The Chess Game – “O jogo de Xadrez” (above, Oil on Canvas, 1943). […] The checkered pattern of the chessboard extends beyond the table not only to the players themselves but also to the very landscape itself […] … Vieira da Silva would have loved The Matrix films […] (more).
Last night I decided to do something new. To play and broadcast live on Twitter, two chess games, blindfold. A 1st one with white pieces, another playing black. For that, I have chosen Chess Titans (link) has my contender, a computer program most people can also access and try out over their PC’s. Chess Titans is a computer chess game developed by Oberon Games and vastly included in Windows Vista and Windows 7. While broadcasting the game live, I added some of my thoughts while playing both games. Even if in brief, that was what I was feeling at the moment: what I was planning, and in what adversary menaces I mostly decided to spent my time.
For those reasons, what follows are those on-the-fly live comments, uncut, made at each moment, while I was thinking. No extra analysis is included here today. It will be more interesting for those who will read me on the future, I guess. This could give a precise idea what happened each time I have made a move, how I react it to some computer moves, and how some of my errors happened as you will see. How my mind went in one direction, or several, depending on the position. Those comments are highlighted by brackets () below, and were twitted live as they arrived to me. Besides, two subsequent comment brackets do not mean two subsequent twitter live chess thinking comments. Sometimes, several minutes have passed between those different thoughts.
As a final note, Chess Titans played each move in around 15-35 seconds, and in difficult positions, rarely, up to 2-3 minutes (I have chosen to play against the maximum level, 10). Playing blindfold, I have spent around 3-4 minutes for regular moves, like exchanging pieces, tweeting, etc, and mostly around 10-15 minutes for some positions, in quite difficult combinatorial patterns. First game playing white, endured 1h and a half (lost it) ,while the second almost 4h and 30 minutes within 58 moves. Here they are:
Game (1) Vitorino Ramos vs. Chess Titans level max.=10 [Sicilian] (LIVE on Twitter 23:00 GMT – 00:24 GMT, Dec. 20, 2012) Duration: 1h 24m.
1. e4, c5 2. c3, Nf6 3. Qc2, e5 4. Ne2, d5 5. exd5, Qxd5 (hmm … 6. d4 or 6.Ng3) 6. d4, Nc6 (7. c4 8. d5 but feeling problems later with his Nb4, Qa4+, Bd7!) 7. dxe5, Nxe5 8. Nf4, Qd7 9. Na3 (for 10. Bb5!), 9. …, Qe7 (was expecting 9. … a6) (10. Be3 seems too bad. Maybe 10. Be2 or Qe2. Or the line 10. Bb5+, Bd7, BxB, Nexd7+, Be3, Ng4 hmm … then Nd5!! ok … 10. Bb5+) 10. Bb5+, Bd7 11. 0-0, (better than BxB+ I guess cause of a future Ng4 by him), 11. …, g5
Chess diagram – crucial position after his 11. …, g5 move. White (me) to play.
(too risky maybe 12. Re1, gxN, Bxf4, Nf6-g4, f3 difficult for me to compute the rest) (12. Re1, gxN, Bxf4, Nf6-g4, f3, … hmm … Nexf3+ ?!!!)
(how about h3; 12. Re1, gxN, Bxf4, Nf6-g4, h3) (hmm???? 12. Re1, gxN, Bxf4, Nf6-g4, h3, Nxf2, Kxf2, Neg4+ ~ hmm) (we also have intermediate variants like, Bxb5, Nxb5, Q moves and gains one tempo by attacking the Knight on b5) (ok, no prob, here I go. This will be bloody …)
12. Re1 12. …, Nf3+ (Oooohhh NO!!!! damn, calculated this more ahead, not now. So stupid) 13. gxf3, Qxe1+ 14. Kg2, gxf4 (now he has Rg8++) (Bxf4 for Rg8+, Bg3 he has QxRa1, bad, bad) 15. Bxd7+, Nxd7 (h3 is an escape now for my King) (16. Rb1, Rg8+, Kh3, Qf1+, Kh4, Be7+ and I think I’m lost) (k, let’s sacrifice the Rook in a1) 16. Bxf4, Qxa1 (at least I have some counter-game now) 17. Qe4+, Be7 (Bd6 will not work due to Rg8+ followed by Qf1+ I guess…, damn, should have played 17. Qe2+!!) (Nb5 menacing Nc7+ or Nd6+ does not work either. Follows Rg8+, Kh3, Qf1+ and Q takes Nb5) (and for Qxb7 he has the robust Rb8 answer) (…. k, the end. Give up. Chess Titans level 10 won 1st game – 2nd game follows) 0-1
After two big blunders on the first game above (the bad 12. Re1 instead of a normal 12. Nd3 – check 1st diagram above -, and 17. Qe4+ instead of 17. Qe2+, since controlling f1 was crucial) the second game did not started well also. After 6 moves I was already losing 1 pawn. Yet, still did manage to open the game and get the initiative a few moves later (around 14. …, Re8+). I feel OK with open and highly combinatorial games as these (normally it’s when I play better), but I forgot one simple fact: I was playing blindfold. Four and an half hours later I guess I’m happy to have managed to drawn a quite interesting and complex game, playing black pieces. What a long and stressful headache. Here:
Game (2) Chess Titans level max.=10 vs. Vitorino Ramos [English opening] (LIVE on Twitter 00:45 GMT – 05:12 GMT, Dec. 20, 2012) Duration: 4h 27m.
1. c4, e5 (English) 2. Nc3, f5 3. g3, c6 4. e4, fxe4 5. Qh5+ (that 4. …, fxe4 was too bad from me. Childish error. Did not see the typical Qh5+ trap, g6, Qxe5+ followed by QxRh8. It should have been 4. …, d6) 5, …, Ke7 6. Qxe5+, Kf7 7. Be2, Qf6 8. Qxe4, Bc5 9. Nf3, Nh6 10. d4 (hmm prepares Ng5+ ??!) 10. …, Bb4 11. Bg5, Qf5 12. Qxf5+, Nxf5 13. Bd3, d6 14. a3, Re8+ 15. Be2, Bxc3+ 16. bxc3, h6 17. Bd2, g5 18. h4, g4 19. Nh2, h5 20. Bf4, b5 21. cxb5, cxb5 22. f3, Bb7 23. Rf1, gxf3 24. Nxf3, Nd7 25. Kd1, a6 26. Ng1, Kg6 27. Re1, Rac8 28. a4 (hmm … Bxh5+ is dangerous if I move the rock in column c, like 28. …, Rxc3), 28. …, Nf6 29. axb5, axb5, 30. Ra7, Bc6 (did calculate Ba8 and Bd5 but hmm, I need d5 for my knight. His bishop on f4 must die) 31. Bd3, Nd5 32. Ne2
Chess diagram – position after his 32. Ne2 move. Black (me) to play. I’m 1 pawn down but with the initiative.
(I can’t take on c3 right? Nxc3, Nxc3, Bf3+, and then he goes back with Knight to e2, gee…) (hard position to mentally calculate) (32. …, b4 ?????) (damn, let me simplify all this…) 32. …, Ra8 33. Rxa8, Rxa8 34. Bxd6 (geee, that 31. Bd3 was so well played) 34. …, Ra1+ (will try to drawn him with successive pressure and checks, I guess) 35. Kd2, Ra2+ 36. Kc1 (yep, he prepares to play Bb1, I guess) 36. …, Nde3 37. Nf4+, Kf7 38. Nxh5, Ra1+ 39. Bb1 (only move for him. If not I change the rocks in e1 with time and then his bishop on d6) 39. …, Be4
Chess diagram – position after my 39. …, Be4 move, pinning b2. White (computer) to play. I’m now 3 pawns down.
(Pinning. Guess this would end with 2 knights and 1 pawn against 1 knight and 4 pawns!!) 40. Kb2, Rxb1+ 41. Rxb1, Bxb1 42. Kxb1, Nxd6 43. Nf4 …
Chess diagram – position after his 43. Nf4 move. Black to play. Now I must stop two different white pawn clusters, on each side. Hard final.
(must be careful, now) (I guess I will do the obvious) (hmm, does not work, 43 …. Ne4 44. Ne2!) (wait, then King on f6, f5, g4 pressing g3) (k, here I go) 43. …, Ne4 44. Ne2, (now, I must think of my pawn on b5, hmm) (he has Ka2, a3 etc) (I have Nc4-d6, hope this helps, … here I go) 44. …, Kf6 45. Kb2, Kf5 46. h5 (?????!!!) 46. …, Kg5 47. h6 (?? He wants my King outside the centre, is that it? … I must take it) 47. …, Kxh6 48. Kb3 (yep, now I have problems on the other side) 48. …, Nd6 49. Kb4 (now my aim will be to arrive on f3 with my King) 49. …, Kg5 50. Kc5, Nec4 (freezing everything!) 51. d5 (hmm, I get it, he wants to reach Kd4 and Kd3. Anyway, I will go for the one in g3) 51. …, Kg4 52. Kc6
(what?????? he is just waiting) (hmm … wait, makes some sense. If 52…, Kf3 then 53. Nd4+, Kxg3 54. Nxb5, Nxb5 55. Kxb5 and I would have 1 knight against 2 pawns and my King far away) (hmm, hard call) (52…, Kf3 or not 52…, Kf3 ??!!!) (Kf3 followed by Ke3 and Kd3 etc does not work also, I think) (… hmm, wait, it might if he does not go Kc5, Kd4. If he goes I will the other way around by Kf4, Ke5)
52. …, Kf3 53. Nd4+, Kxg3 54. Kc5, Kf4 55. Nxb5, Ke5 (and it’s a drawn, I guess) 56. Kb4, Nxb5 57. Kxc4 57. …, Nxc3 ( if he goes 58. d6 then 58. …, Nd5! 59. d7, Nb6+ followed by Nxd7!!) 58. Kxc3, Kxd5 ½–½ (uuuufff, managing to draw blindfold, is a good result I guess :)
One of my conclusions: never play blindfold again in a open and highly combinatorial position, namely when you have a pair of knights. That, could make you dizzy and sick. Another (among, many others): never live tweet chess again. You will loose a lot of dumb followers (which turns-out to be healthy) and simultaneously attract all kinds of weirdos, and guru-like spam on-line marketeers. Vieira da Silva was right. It extends beyond the table. Like lake ripples when a stone is thrown.
Figure – Brain wave patterns (gamma-waves above 40 Hz). Gamma waves – 40 hz above – these are use for higher mental activity such as for problem solving, consciousness, fear. Beta waves – 13-39 Hz – these are for active thinking and active concentration, paranoia, cognition and arousal. Alpha waves – 7-13 Hz – these are for pre-sleep and pre-wake drowsiness and for relaxation. Theta waves – 4-7 Hz – these are for deep meditation, relaxation, dreams and rapid eye movement (REM) sleep. Delta waves – 4 Hz and below are for loss of body awareness and deep dreamless sleep (source: Medical School, link).
Figure – Paul Klee painted this work in 1930-1931. He entitled it “Super Schach” (Super Chess). On his own way he was a remarkable visionary. It’s all about patterns, and relations between them. Frequently perceived in a few milliseconds. While playing, sometimes, I see the board almost like this, as only few pieces were there, and important places in the board at that precise moment were painted in vivid blue. Tilting to us on a special manner. Calling us, like a pointillist painting does.
“The problem for me is the playoff will begin at 3AM my time. So you all better send lots of coffee which I don’t drink :)” – @brandnewAMIT have red bull instead, it’ll give you wings :) – “I’m probably the most boring GM ever. I don’t smoke or drink, not even red bull. Always try to eat healthy food and work out.” ~ Susan Polgar over Twitter on May 28, 2012. (link)
“Whoever denies the high physical effort of a tournament player doesn’t know what he’s talking about. Many examinations prove that heart, frequency of breathing, blood pressure and skin are subjected to great strain, weight losses appear during a tournament – so chess players need a special way of life with regular training, practice of other keep-fit activities and healthy diet.”, Dr Willi Weyer speech on the 100th anniversary of the German chess federation in Bad Lauterberg on 12 March 1977.
[…] Cuenta la leyenda que segundos antes de llegar a una curva, Juan Manuel Fangio dirigía una fugaz mirada a las hojas de los árboles. Si se movían, levantaba el pie del acelerador; si, por el contrario, no soplaba el viento, pisaba a fondo. […], in Ángel Luis Menéndez, “Los abuelos de Alonso”, Público.es (link)
In a few hours, today, one of the most dramatic high-tension “F1 car races” ever will start. Though, it’s not only about sport, it will be about science, art, drift spatial aesthetics and psychology as well, … altogether taken to their very extreme. And, at the limit, it will end-up being about how two very different people and human characters behave while confronting each other trough puzzling millisecond brainwaves. While the hot race is on, I will be watching the board carefully, of course, but mainly – let me add – their faces. It’s their human side over an intensive battle, that ultimately interests me, and always pushes forward my focal attention.
For those who are not used to deal with high incommensurable pressure and stress while the clock is fast ticking, or ever educated themselves along their lives to perform with “grace under fire“, far behind their technical know-how something unique over an athlete, probably it will be hard to understand, among other things, why F1 and chess have so many things in common, and are in fact, so close to each other. Breathing in many sports are fundamental. In chess, it’s crucial.
It will be hard to imagine, for instance, that a regular chess player under enormous stress could loose up to 4Kg, just in one single important game, where everything is at stake. Not counting the increasing exponential adrenaline levels he must support (e.g. 772% on figure below), sometimes for long periods of time contrary to other – surprise, yourself – “soft” sports. It’s brutal: ” (…) It’s chess. Many don’t think of it as a sport, because nobody moves. But Chess Masters will tell you it can be more brutal than boxing (…)”, in CBS 60 minutes “Mozart of Chess” (YouTube link), CBS news entry piece on Magnus Carlsen, last year.
photo – Anand looking pensive to Gelfand at the end of the last 12th game, deciding for the final tiebreaks. [Allow me to add one of his possible thoughts: “It’s all about quick risky moves now, Boris. No more chicken play-to-draw games ” (Source: http://moscow2012.fide.com/en/ )].
The apparently illogical link between chess, F1 drivers and F16 jet pilots at war does not end here, however. Unfortunately, they also come from the dark side. Increasingly rumors state that all this areas might be related by the use of PED’s, by some cheaters. The answer again, comes from what this human-activity areas desperately need. They need fast strategic and tactic responses, as well as imagination to surprise the adversary, while maintaining extreme accuracy. All those three characteristics tied together, think of it … that’s something very hard and uncommonly rare to find in us, Humans. For curiosity, just have a look on what an UK steroids company states:
(….) There has been reports of performance enhancing drugs being used in the game of chess. Now anabolic steroids and a ripped physique will not increase your mental capacity, but some drugs can be used to control blood pressure and meditate heart beat allowing a more controlled and balanced state of mind. Testing in Formula One has even been taken to a new level. Since F1 brought its drug testing standards up to the level required by the World Doping Agency, drug testing has been more thorough and more frequent. (…) in (link).
Performance enhancing drugs (PED’s) have been reported, mainly by the use of beta-blockers. Beta-blockers are known to slow heart rate, as well as adrenaline, while maintaining the other brain functions on, and quick. At F1, on F16 fighters, on chess as well as in science, as in some of our regular daily digital software life (yes, Nasdaq High-frequency trading are targets now), digital doping is also possible. Injecting performance-enhancing code seems unfortunately to be a current trend. Just recently I have testimony this over an Iterated Prisoner’s Dilemma online contest my-self.
Allow me however to drag you onto the healthy positive side and draw your attention to one MSc thesis entitled “Practical Recommendations to Chess Players from Sports Science” (PDF link) which I recommend to friends for long years now. From coffee (pp. 9) to beta-blockers (pp. 13), Kevin O’Connell (University of Essex; MSc Sports Science Dissertation, 1997) discusses several important issues. Here are some brief excerpts from his thesis:
(…) In connection with which I find it interesting to recall remarks made to me by a couple of chess players, one who used to play as a striker for the Norwegian national soccer team before being forcibly retired by a cruciate ligament injury and by a Chilean tennis professional who made it into the world’s top 50 as a tennis player, that chess is a harder sport, physically, than either of their other occupations. (…) Andreassi (1995) reported evidence that brain activity is influenced by cardiac events, “for example, the decreased HR that occurs under instructions to detect signals leads to a decrease in the inhibitory influence of baroreceptors on cortical function, resulting in enhanced brain activity and improved performance.” (…)
(…) It is clear that fatigue is a major contributory cause of error in chess and that two of the five main metabolic causes of human fatigue (Newsholrne, 1995) are potentially relevant. These are the decrease of blood glucose concentration and an increase in the concentration ratio of the free tryptophan to branched chain amino acids in the bloodstream. (…) In brief, the central fatigue hypothesis (after Newsholme, 1995) runs as follows. During exercise there is an elevation in the blood adrenaline level and a decrease in that of insulin which results in fatty acid mobilization from adipose tissue, consequently increasing the level of fatty acids in plasma (formula one racing drivers, who experience similar adrenaline levels to chess players, have been noted for their ‘milky’ plasma). (…)
Figure – (…) The heart rates measured by Hollinsky‘s team included peaks in excess of 220/min and a single maximum of 223/min. Table 2 shows the HR, and blood pressure graph for a player 27 years old and rated 2064 over the course of one game, from six p.m. until its conclusion just after midnight. Not surprisingly, at least to chess players, the peak HR is reached in the time-pressure phase towards the end of the sixth hour of play (…) (from K. O’Connell MSc thesis, link above).
Today however, at the Tretyakov state art gallery in Moscow (link), all these will happen quite fast, in just tiny seconds, while the whole world will be watching live. The actual champion Viswanathan Anand (defending his title) will have to fight it out in rapid chess tiebreaker against challenger Boris Gelfand after a tied 6-6 result in the World Chess Championship match. Both, now arrive at a situation when the match cannot be prolonged any further. To start with, there will be four games under rapid chess rules with 25 minutes to each player and a ten seconds increment after every move is made. In case of a 2-2 result, the two will play two blitz games with five minutes each with a three seconds increment per move.
Between them, Anand and Gelfand have in the past played 28 times in rapid chess and the Indian has won eight, lost one and drawn the remaining. In blitz, they have played seven games with three wins for Anand and the rest being drawn. Today, there will be five such matches if the tie persists and finally an Armageddon game will be played with five minutes to white and four to black and white will be forced to win should this arise. The whole fast race could be followed live at http://moscow2012.fide.com/en/ while the board, analysis, chat, etc here at http://livechess.chessdom.com/site/ . Games will start at 10:00 AM CET. I would guess both players are having their “beauty sleep” right now.
Today, the world chess champion will be known. It’s about all of us, Humans. Taken to our creative limits. As Fangio, even if the pressure is considerably high, always take a look at the trees surrounding you. If you blink, you will just miss it.
Make yourself an exercise. Have a glimpse again on Klee‘s Super Schach. Starting from the bottom left corner, count 6 squares to the right. Then, look precisely above at the second row. What’s that?! See it?!
The importance of Network Topology again… at [PLoS]. Abstract: […] The performance of information processing systems, from artificial neural networks to natural neuronal ensembles, depends heavily on the underlying system architecture. In this study, we compare the performance of parallel and layered network architectures during sequential tasks that require both acquisition and retention of information, thereby identifying tradeoffs between learning and memory processes. During the task of supervised, sequential function approximation, networks produce and adapt representations of external information. Performance is evaluated by statistically analyzing the error in these representations while varying the initial network state, the structure of the external information, and the time given to learn the information. We link performance to complexity in network architecture by characterizing local error landscape curvature. We find that variations in error landscape structure give rise to tradeoffs in performance; these include the ability of the network to maximize accuracy versus minimize inaccuracy and produce specific versus generalizable representations of information. Parallel networks generate smooth error landscapes with deep, narrow minima, enabling them to find highly specific representations given sufficient time. While accurate, however, these representations are difficult to generalize. In contrast, layered networks generate rough error landscapes with a variety of local minima, allowing them to quickly find coarse representations. Although less accurate, these representations are easily adaptable. The presence of measurable performance tradeoffs in both layered and parallel networks has implications for understanding the behavior of a wide variety of natural and artificial learning systems. […] (*)
(*) in Hermundstad AM, Brown KS, Bassett DS, Carlson JM, 2011 Learning, Memory, and the Role of Neural Network Architecture. PLoS Comput Biol 7(6): e1002063. doi:10.1371/journal.pcbi.1002063
Figure – Understanding the Brain as a Computational Network: significant neuronal motifs of size 3. Most over-represented colored motifs of size 3 in the C. elegans complex neuronal network. Green: sensory neuron; blue: motor neuron; red: interneuron. Arrows represent direction that the signal travels between the two cells. (from Adami et al. 2011 [Ref. below])
Abstract: […] Complex networks can often be decomposed into less complex sub-networks whose structures can give hints about the functional organization of the network as a whole. However, these structural motifs can only tell one part of the functional story because in this analysis each node and edge is treated on an equal footing. In real networks, two motifs that are topologically identical but whose nodes perform very different functions will play very different roles in the network. Here, we combine structural information derived from the topology of the neuronal network of the nematode C. elegans with information about the biological function of these nodes, thus coloring nodes by function. We discover that particular colorations of motifs are significantly more abundant in the worm brain than expected by chance, and have particular computational functions that emphasize the feed-forward structure of information processing in the network, while evading feedback loops. Interneurons are strongly over-represented among the common motifs, supporting the notion that these motifs process and transduce the information from the sensor neurons towards the muscles. Some of the most common motifs identified in the search for significant colored motifs play a crucial role in the system of neurons controlling the worm’s locomotion. The analysis of complex networks in terms of colored motifs combines two independent data sets to generate insight about these networks that cannot be obtained with either data set alone. The method is general and should allow a decomposition of any complex networks into its functional (rather than topological) motifs as long as both wiring and functional information is available. […] from Qian J, Hintze A, Adami C (2011) Colored Motifs Reveal Computational Building Blocks in the C. elegans Brain, PLoS ONE 6(3): e17013. doi:10.1371/journal.pone.0017013
[…] The role of evolution in producing these patterns is clear, said Adami. “Selection favors those motifs that impart high fitness to the organism, and suppresses those that work against the task at hand.” In this way, the efficient and highly functional motifs (such as the sensory neuron-interneuron-motor neuron motif) are very common in the nervous system, while those that would waste energy and give no benefit to, or even harm, the animal are not found in the network. “Adami and his team have used evolutionary computation to develop hypotheses about the evolution of neural circuits and find, for these nematode worms, that simplicity is the rule,” says George Gilchrist, program director in NSF’s Division of Environmental Biology (in the Directorate for Biological Sciences), which funds BEACON. “By including functional information about each node in the circuit, they have begun decoding the role of natural selection in shaping the architecture of neural circuits.” […] from Danielle J. Whittaker “Understanding the Brain as a Computational Network“, NSF, April 2011.
Time-lapse imaging in live zebrafish embryos reveals that cerebellar granule cells migrate in chain-like structures as discovered by a recent article [1] [Köster et al., PLoS, Nov. 2009]. Figure above – Granule cells taken from the cerebellum of a pigeon (above, B) are shown in this 1899 drawing by legendary neuroscientist Santiago Ramón y Cajal.
Did talk about sticky objects and self-organization in the past, how positive and negative feedback’s stigmergic-like agents integrated could promote changes and learning over a complex system. Same happens to bacteria as also ants. On the other hand, we do know memes are also sticky (e.g. Chip Heath, Dan Heath, “Made to Stick: Why Some Ideas Survive and Others Die“, Random House, ISBN 978-1-4000-6428-1, January 2007). What’s new however, is that there are increasing proofs that our own brains my follow similar mechanisms (as Douglas Hofstadter in the past did made some analogies with how brains could work and how ant colonies raid different environments). In this recent new study, Köster and colleagues [1] [PLoS, Nov. 2009] reveal crucial pieces of this puzzle, showing how (neuronal) cells orient themselves to migrate together (like bacteria, above). The team studied zebrafish, one of the workhorses of developmental neurobiology, because its transparent body allows researchers to track movements of cells inside of it. As explained by Mason Inman [2]:
[…] Neurons in the developing brain complete their own self-organized waltz, coordinating with their neighbors to migrate to the right spots to form the cerebellum, visual cortex, or other parts of the brain. In this issue of PLoS Biology, Reinhard Köster and colleagues show that some of these brain cells behave much like slime molds, coordinating with other cells of the same type to migrate in a herd. They found that one particular protein called Cadherin-2 is crucial in allowing the cells to adhere to their neighbors so they can coordinate their movements and all wind up in the right spot. […] Slime molds provide a textbook example of self-organization. They live as single cells until food becomes scarce. Then, they broadcast chemical signals that trigger their mass assembly into a fruiting body, with some cells forming a stalk and others turning into spores that cast about in the winds to spread far and wide. […] Neurons in the developing brain complete their own self-organized waltz, coordinating with their neighbors to migrate to the right spots to form the cerebellum, visual cortex, or other parts of the brain. In this issue of PLoS Biology, Reinhard Köster and colleagues show that some of these brain cells behave much like slime molds, coordinating with other cells of the same type to migrate in a herd. They found that one particular protein called Cadherin-2 is crucial in allowing the cells to adhere to their neighbors so they can coordinate their movements and all wind up in the right spot.[…]
[…] But the mechanisms behind this coordinated movement – in particular, how each cell adjusts its inner workings to move to the right place at the right time – are only now starting to be revealed, using imaging that tracks these cells in live animals as they develop. […] To figure out what triggers the cells to line up and move together, the authors looked at what other kinds of cells were in the neighborhood. Many studies have shown that support cells, known as glial cells, often help guide neurons during these kinds of migrations. But during the first few days of the zebrafish embryo’s development, Köster and colleagues found, there were no glial cells along the granular cells’ migration route. That means these cells must go it alone, the team reasoned, with their own mechanism for signaling between each other to line up into chains and make their move. […] Although the study focused on just one type of brain cell, the findings could explain how many types of neurons find their way to their proper spots as the brain develops. There are still some pieces of the puzzle missing, however. While the findings explain how the granule cells are able to coordinate and follow their neighbors, it’s still not clear how the first few cells to head out on the journey – those at the front of the “conga line” – get oriented in the right direction. This suggests there must be some kind of signal from surrounding cells to get them headed in the right direction, the authors argue – yet another level of organization. […] , in Mason Inman (Nov., 2009) Migrating Brain Cells Stick Together, PloS. [2]
[1] Rieger S, Senghaas N, Walch A, Köster RW (Nov., 2009) Cadherin-2 Controls Directional Chain Migration of Cerebellar Granule Neurons. PLoS Biology.
[2] Mason Inman (Nov., 2009) Migrating Brain Cells Stick Together, PloS Biology.
Chemoton § Vitorino Ramos' research notebook 
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