A Zombie’s Inquiry Into the Evolution of his Most Favorite Meal II

In my last post I listed some important factors in the evolution of the human brain, or better imagined what a zombie evolutionary biologist, named George, might dig up when investigating the evolutionary path of his Dinner Nr. 1. As Terrence Deacon (1997) puts it, there is no escaping the fact that human brains are unusually large. There are several factors why humans could develop large brains, but what is still at stake is the question why they actually did, and how they came into a position that allowed them to devote so much energy to a walnut-shaped pink lump of tissue with the consistency of a half-baked egg.
This question is critical, because organisms do not normally develop new traits just because they can. This of course also happens, in combination with random genetic drift and populations bottlenecks. But because evolution is a ‘miserable and greedy tinkerer’, or put more nicely, an economical process, it is highly unlikely that it produces needless and incredibly complex capacities that are extremely costly to maintain. As a consequence,

“some proportionately beneficial advantage must have driven brain evolution against the steep selection gradient created by the high costs of brain tissue.” (Dunbar & Shultz 2007)

Why, Dunbar and Shultz ask further, do primates have so much bigger brains than squirrel, with both facing about the same foraging decisions? (Dunbar & Shultz argue that ecological explanations fail to account for this differences, but their Chimpanzee-Squirrel dichotomy nevertheless is a bit hyperbolical, given that, among primates, those whose diet includes insects and fruits show higher encephalization rates than leaf-eaters, and strategic hunting and gathering of food and prey places additional demands on navigational, representational and other cognitive skills. However, their general argument is still valid. (Park et al. 2007))

To shed light on this issue, we can divide the big picture into several smaller ones. Useful questions include: What are we good at? Split into What are we (primates) good at? And What are we (humans) even better at than other primates? What could the ecological niche favoring big brains in humans have looked like? How exactly does our brain differ from that of other primates?
These questions essentially depend on comparative ethology (how do our minds work compared to how the minds of other animals work?), comparative (neuro)anatomy (On which evolutionary foundations are our modern cognitive abilities, and other phenotypic traits built upon?), and the kind of scenario we envision or infer from these observations togther with the fossil record and other lines of evidence. Of course it is also crucial what we think what the most salient and essentially aspects of our ancestors were. Do we see our ancestor as “Man the Tool Maker”, “Man the Hunter” or “Man the Social Animal”, or just as “Man with the extraordinarily big & expensive (and extremely delicious, George might add) brain”.

Well, of course Man should probably rather be seen as “Man the cooperative, competitive, tool-making, hunting, {…}, articulate social animal.” And all of these property probably contributed (co-evolutionary, we might say, without adding much in terms of explanatory adequacy) to our cognitive abilities and brain size, but in which order? And which driving forces were a little more pushy than others?
As Cheney & Seyfarth (2007) have show in baboons, interactions in primate groups are cognitively highly demanding and require sophisticated representational and predictive abilities, because of the intricate and complex networks and ‘friendships’ they inherit. Thus rising complexity in social life could be seen as a key selection pressure in the evolution of cognitive abilities in primates in general, and especially in humans. (Lewin 2005: 220f.)
Depending on which aspect one wants to stress, this correlations can be described in different terms. Scholars who wanted to stress the competitive aspect of social life dubbed it the “Machiavellian Intelligence Hypothesis.” (Byrne & Whiten 1988: who themselves, interestingly, didn’t want to stress the competitive aspect by giving the hypothesis the title). Now it is most widely called the “Social Brain Hypothesis” to emphasize the general complexity of primate groups including all arising affordances (Dunbar 1998, Dunbar & Shultz 2007).
Unfortunately, this is still rather vague. To get a clearer picture, it is important to make explicit the advantages and disadvantages of large social groups and the specific problems which need to be solved. However, group size indeed seem to contribute advantageously to genetic fitness by minimizing predation risk, but paired with greater ecological and reproductive competition and suppression, affording higher behavioral flexibility (Dunbar & Shultz 2007). Brain expansion theories stressing the importance of ’technological intelligence’ as a driving force. (without neglecting the importance of social factors, but seeing the latter as less crucial). According to these views, the ‘behavioral drive’ for cultural transmission and innovation is more frequent in species with large brains. As a consequence these species are led to exploit the environment in new way, opening up new possibilities regarding new selective pressures. ´(Reader and Laland 2002). Certainly, these tendencies were important, but where do they come from? Big-brains seem to be a prerequisite for ‘technological intelligence’, but how did these evolve in the first place? Rather it seems probable that

“Although innovation, tool use, and technological invention may have played a crucial role in the evolution of ape and human brains, these skills were probably built upon mental computations that had their origins and foundations in social interactions.” (Cheney & Seyfarth 2007: 283).

Supporting Reader and Laland’s emphasis on the importance of technological aspects on human cognitive evolution, Tomasello and his colleagues propose that human’s advanced Theory of Mind-skills were amplified not in the context of intention-reading present in great apes, but rather during learning and imitation of hierarchical planned and structured tool-making and tool-using. (Tomasello et al. 2005: 687). I’m not sure whether George would like this speculation. Probably, he would argue this to be a ‘just-so story’ and propose that all scientist coming up with these should be eaten. So thank God scientists are not really zombies, I wouldn’t miss the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany (and especially its co-director) for anything in the world (OK, except for the really important things such as love, life, family, donuts.

I haven’t addressed much of the questions stated in the beginning, especially What we as humans are especially better at than other primates. I will come to this issue in my next post (relying again on research done by scientists from the Max Planck Institute for Evolutionary Anthropology, so again, glad they haven’t been eaten.)

References:

Cheney, Dorothy L. and Robert M. Seyfarth. 2007. Baboon Metaphysics: The Evolution of a Social Mind. Chicago: University of Chicago Press.

Deacon, Terrence William 1998. The Symbolic Species. The Co-evolution ofLanguage and the Brain. New York / London: W.W. Norton

Dunbar, Robin I.M.1998.“The Social Brain Hypothesis” Evolutionary Anthropology 6: 178-190.

Dunbar, R. I. M. and Susanne Shultz. 2007.“Evolution in the Social Brain” Science 317: 1344-1347

Park, Min S., Andrew D. Nguyen, Henry E. Aryan, Hoi Sang U, Michael L. Levy, Katerina Semendeferi. 2007. “Evolution of the Human Brain: Changing Brain Size and the Fossil Record.” Neurosurgery 60:555–562.

Reader, S.M. and K.N. Laland. 2002. “Social Intelligence, innovation, and enhanced brain size in primates” PNAS 99: 4436-4441

Tomasello, Michael, Malinda Carpenter, Josep Call, Tanya Behne, and Henrike Moll. 2004. “Understanding and Sharing Intentions: The Origins of Cultural Cognition.” Behavioral and Brain Sciences 28

Zombies have Taste

In my last post I wrote about the fact that human brains are selfish energy-hungry little bastards, which makes the stuff they’re made of extremely ‘expensive tissue’ (Aiello & Wheeler 1995). This means that zombies have a quite extraordinary taste, equivalent to a caviar-gourmet (either that, or they are ‘informavores’ just like we are (Miller 1991)).
Now imagine (instead of the oft-cited martian scientist) a zombie-evolutionary biologist (Insert joke about the parasitic tendencies of the ‘mindless new atheism’ and/or Intelligent Design, the Idea of theistic evolution, greedy reductionism, Evolutionary Psychology or whatever floats you boat here) puzzling over the evolutionary emergence of his most favorite meal. Let’s take it for granted that our zombie-scientist is not easily satisfied by zombie-centric evolutionary concepts, just as Steven Pinker warns us that, if Elephants were the most culturally advanced species (well, and maybe they are, who knows), their evolutionary biologist (albeit only the bad ones) would probably search for the evolutionary path that inevitably climaxed in the highest form, the evolutionary optimum of trunkitude. Let’s also assume our zombie-scientist isn’t a friend of ‘just-so’ stories like ‘humans evolved bigger brains to run away from zombies more effectively’. Assuming, too, that human scientist like Aiello, Wheeler, Dunbar and others weren’t eaten before publishing their caveats about the expensiveness of brain evolution and maintenance, or that some other zombie-scientists could hold back their hunger long enough to test human subjects before eating them, coming to similar conclusions as Aiello and others did – or, rather would have come if they hadn’t been eaten beforehand. Assuming this, we could be sure that our zombie-scientist would not regard the evolution of a ‘general being-eaten-avoidance intelligence’ as unlikely.

What then, our zombie-scientist, call him George, would ask, was the reason humans developed such large, specialized brains. Looking for homologues or convergent evolution in other (hopefully not entirely eat… I mean extinct) species, and considering what makes the human mind special. George could come up with a lot of possible hypotheses as driving forces and triggers of brain evolution, and other facts he would have a hard time to make sense of such as:

• positively selected genes involved in regulating (Microcephalin: Evans et al. 2005) and determining brain size (ASPM: Mekel-Brobov et al. 2005), development of the human neocortex (HAR1F: Pollard et al. 2006), and playing a part in progressive changes in cognitive abilities (Neuropsin: Li et al. 2004)
  
• 
  
• cooking, paired with gastrointestinal shrinkage (our intestinal tract is only 60% the size expected of a primate with similar size) may have saved energy from digestion which in turn could be used to help fuel the brain. Together with the possible role of meat and more efficient upright walking and running, this could have expanded the human energy budget significantly (Gibbons 2007)
  
• 
  
• supporting this hypothesis, AMY1, a gene improving the digestion of food containing starch, is found in much greater numbers in humans than in chimpanzees (Perry et al. 2007)
  
• 
  
• Correlations between group size and neocortex size (Dunbar 1993, Dunbar & Shultz 2007) on the one hand, and significant positive correlation between innovation, social learning, tool use and brain size on the other, (Reader and Laland 2002, Reader 2003), making it likely that social and technological innovative intelligence (mediated by social learning) both played a crucial and inseparable role in human brain evolution (Cheney & Seyfarth 2007)
  
• 
  
• The possibility that the ability to evolve fat babies was the precursor for the evolution of the big and metabolically expensive brain (The article proposing this hypothesis is called ‘survival of the fattest’, What a great pun! Er… or maybe not) . In a resting newborn baby, the brain consumes 74% of the baby’s energy intake. In a 4-6 months old baby the rate is 64%, further dropping during ontogenetic development until reaching a rate of about 23% in adults. And whereas in chimpanzee infants, there is virtually no body fat, in human infants body fat contributes about 11-14% of the baby’s weight (as does the baby’s brain) (Cunnane & Crawford 2003)
  

So one thing is clear: a stable high-energy food supply was essentially necessary for human brain development, as were the possibility for longer ontogenetic development (as often observed, human (and generally primate) newborns are pretty much helpless compared to newborns of other species, with some even able to walk following almost immediately after birth).
Another important aspect is the general tendency in mammals to develop bigger brains compared to other species (they are about 10 times ‘brainier’ than amphibians or reptiles). Then, humans are part of the order of primates, which (along with toothed whales) have bigger brains than other mammals. And among primates, monkeys and apes have the biggest brains. But, as I said, our brains are even three times bigger than that expected of an ape of similar size. Another factor is the fact that the pre-natal rapid brain growth observed in other species whose infants are relatively helpless continues post-natally in human babies for about twelve months instead of changing into a slower pace.
As a consequence, human infants are even more helpless than that of other primates. This requires a much greater devotion of time, energy and other resources from the parent’s side. (Lewin 2005: 217f., John L. Locke and Barry Bogin (2005) make a similar argument concerning the unique human life history and ontogenetic development, but extending it not only to brain growth in general, but also to the evolution of language).
Making such a list, George would probably have a lot of trouble to distinguish preconditions, epiphenomena, co-evolutionary processes and driving forces of brain expansion. In my next post I will try to shed some light on this issue (Of course I will fail even more grotesquely than someone who is not a complete layman, but I hope that I will at least clarify some points)

References:

References:

Aiello L.C. and P. Wheeler 1995. ”The expensive tissue hypothesis: the brain and the digestive system in human and primate evolution.” Current Anthropology 36:199–221

Cheney, Dorothy L. and Robert M. Seyfarth. 2007. Baboon Metaphysics: The Evolution of a Social Mind. Chicago: University of Chicago Press.

Cunnane Stephen C. and Michael A. Crawford. 2003. “Survival of the fattest: fat babies were the key to evolution.” Comparative Biochemistry and Physiology Part A: 136.1: 17-26

Dunbar, R.I.M. 1993. “Co-evolution of Neocortex size, group size and language in humans.” Behavioral and Brain Sciences 16.4: 681-735

Dunbar, R. I. M. and Susanne Shultz. 2007.“Evolution in the Social Brain” Science 317: 1344-1347

Evans, Patrick D., Sandra L. Gilbert, Nitzan Mekel-Bobrov, Eric J. Vallender, Jeffrey R. Anderson, Leila M. Vaez-Azizi, Sarah A. Tishkoff, Richard R. Hudson, Bruce T. Lahn “Microcephalin, a Gene Regulating Brain Size, Continues to Evolve Adaptively in Humans” Science 309: 1717-1720.

Gibbons, Ann. 2007. “Food for Thought.” Science 316. 1558-1560.

Lewin, Roger. 2005. Human Evolution: An Illustrated Introduction. Fifth Edition. Suffolk: Blackwell.

Locke, John L. and Barry Bogin. 2005. “Language and life history: A new perspective on the development and evolution of human language” Behavioral and Brain Sciences

Mekel-Bobrov, Nitzan, Sandra L. Gilbert, Patrick D. Evans, Eric J. Vallender, Jeffrey R. Anderson, Richard R. Hudson, Sarah A. Tishkoff, Bruce T. Lahn. “Ongoing Adaptive Evolution of ASPM, a Brain Size Determinant in Homo sapiens.” Science 309: 1720-1722

Li, Yi, Ya-ping Qian, Xiao-jing Yu,* Yin-qiu Wang, Ding-gui Dong’ Wei Sun, Run-mei Ma and Bing Su. 2004. “Recent Origin of a Hominoid-Specific Splice Form of Neuropsin, a Gene Involved in Learning and Memory.“ Molecular Biology and Evolution 21.11: 2111-2115.

Miller, G.A. 1991. The Science of Words. New York: W.H. Freeman

Reader, S.M. 2003. “Relative brain size and the distribution of innovation and social learning across the nonhuman primates.” The Biology of Traditions: Models and Evidence. Eds. D.M. Fragaszy and S. Perry, 56-93.

Reader, S.M. and K.N. Laland. 2002. “Social Intelligence, innovation, and enhanced brain size in primates” PNAS 99: 4436-4441.

Pollard, Katherine S., Sofie R. Salama, Nelle Lambert, Marie-Alexandra Lambot4, Sandra Coppens, Jakob S. Pedersen, Sol Katzman, Bryan King, Courtney Onodera, Adam Siepel, Andrew D. Kern, Colette Dehay, Haller Igel, Manuel Ares Jr, Pierre Vanderhaeghen & David Haussler. 2006 “An RNA gene expressed during cortical development evolved rapidly in humans.” Nature 443: 167-172.

Perry, George H, Nathaniel J Dominy, Katrina G Claw, Arthur S Lee, Heike Fiegler, Richard Redon, John Werner, Fernando A Villanea, Joanna L Mountain, Rajeev Misra, Nigel P Carter, Charles Lee, & Anne C Stone. 2007 “Diet and the evolution of human amylase gene copy number variation“ Nature Genetics Advanced Online Publication doi :10.1038/ng2123

Brains are Expensive

A while back, Larry Moran over at the Sandwalk wrote about previous expectations of scientist about the number of genes in the human genome. (See also his discussion of Pennisi 2005) The guesses ranged from 140,000 to 15,000 genes. Reading this I was reminded of a statement from Thompson (2001) which I quoted in a term paper about language evolution: 30,000 to 50,000 genes of the human DNA are present in all cells, but only activated in brain cells. This would be a quite extraordinary feat, given that there seem to be only about 20,488 genes at all in the human genome. (Pennisi 2007). But there are other statements that characterize the ‘hyperastronomical’ dimensions (Quine 1987) of the brain quite well. (Quine used the word when describing the vastness of Borges’ fictional Library of Babel, a universe-sized library which contains books with all possible combinations of characters there are, making it impossible to find even one comprehensible sentence. But as a complete layman, I sure sometimes feel the same when reading an article about neuroscience… or anything else for that matter)

The Brain consists of an incredible 10¹⁰ neurons and 10¹³ synapses (Gegenfurtner 2005) and the number of possible connectional combinations between is sometimes estimated to be greater than the number of molecules in the universe (Ramachandran) no wonder it is sometimes called the most complex structure in the know universe. Further, with its about 1251.8 cubic centimeters (cc) (compared to the 316.7 cc of greater apes) (Rilling 2006),our brain is about three times bigger than that of an ape would be, given the same body-size (Lewin 2005).
Just as remarkable is the amount of energy the brain consumes. Although the human brain weighs only 2% of an adult’s body weight, it accounts for 20-25% of its resting energy intake. As a comparison, a chimpanzee’s brain only consumes about 8-9% of its resting metabolism. Thus, the brain uses energy at the same rate consumed by leg muscles of a marathon runner when running (Attwell & Laughlin 2001. It seems like that one could make a good joke out of this fact, but sadly I can’t really imagine how.) The costs to run a human brain are, per unit mass, about 8 to 10 times higher than those for skeletal muscles. In the energy-consuming business, it is only topped by the heart. (Dunbar & Shultz 2007).

At the moment there doesn’t seem to be enough data to estimate which brain areas consume how much energy, but there are two promising candidates for the title of ‘hungriest brain area’. 50% to 60% of the human cerebral cortex are devoted to the perception and interpretation of visual stimuli and the reactions to it. Given that, perception is an incredibly complicated and complex task, this seems quite understandable: In sum, the brain receives about two gigabyte of data per second from approximately 200 million photo receptors in the eyes (Gegenfurtner 2005). Another aspirant for the title are the auditory areas, where metabolic rates seem to be 40% greater than in other parts of the brain (Attwell & Laughlin 2001).
Brains really are made out of “expensive tissue” (Aiello & Wheeler 1995). Because of this, specialized intelligence is far more likely to be created by natural selection than general intelligence, or a brain that is ‘just large’ due to the sheer cost of evolving and maintaining such a thing. (Cheney & Seyfarth 2007: 11) (Ha! Suck on this Jean Piaget! ;) ) As Robin Dunbar puts it: “Because the cost of maintaining a large brain is so great, it is intrinsically unlikely that large brains will evolve merely because they can. Large brains will evolve only when the selection factor in their favor is sufficient to overcome the steep cost gradient“ (Dunbar 1998: 179). In my next post I will consider some of the proposals why we do have such damn hungry and huge brains.

References:

Aiello L.C. and P. Wheeler 1995. ”The expensive tissue hypothesis: the brain and the digestive system in human and primate evolution.” Current Anthropology 36:199–221

Attwell, David and Simon B. Laughlin. 2001. “An Energy Budget for Signaling in the Grey Matter of the Brain.” Journal of Cerebral Blood Flow and Metabolism 21:1133–1145.

Dunbar, Robin I.M.1998.“The Social Brain Hypothesis” Evolutionary Anthropology 6: 178-190.

Dunbar, R.I.M. and Susanne Shultz. 2007. .“Evolution in the Social Brain” Science 317: 1344-1347

Lewin, Roger. 2005. Human Evolution: An Illustrated Introduction. Fifth Edition. Suffolk: Blackwell.

Quine, W. V. 1987. Quiddities: An Intermittently Philosophical Dictionary. Cambridge, MA: Belknap Press

Pennisis, Elizabeth. 2005. "Why do Humans have so Few Genes?" Science 309: 80.

Pennisis, Elizabeth. 2007. "Working the (Gene Count) Numbers: Finally, a Firm Answer?" Science 316: 1113.

Rilling, James K. 2006. Human and NonHuman Primate Brains: Are They Allometrically Scaled Versions of the Same Design? Evolutionary Anthropology 15: 67-77.

Thompson, Richard F. 2000. The Brain: A Neuroscience Primer. Third Edition. New York: Worth Publishers.

Evolutionary Metaphysics V

So this is my last post about “Baboon Metaphysics” and what we get if we try to combine it with some other lines of research. Now which steps were necessary for the evolution of the human mind and language, and in which order?
As a starter, our LCAs with chimpanzees should have exhibited or later evolved the following traits:

1 A rudimentary Theory-of-Mind and a conceptual system which enabled them to form multimodal mental-representations had to be present (Cheney & Seyfarth 2007, Barsalou 2005, Gil-da-Costa et al. 2004)

2a enhanced displaced conceptual control somehow evolved, probably due to prefrontal enlargement, resulting in higher frontal control over neural processes (Barsalou 2005, Deacon 1998, Miller et al. 2002, Rilling 2006)

2b enhanced ToM-abilities, probably influenced by greater frontal control, but also due to some elaboration of an existing mirror neuron system (which is present, for example in maqaques) which then was integrated into a higher order system together with cortical midline structures responsible for social and self-evaluation and possibly other information structures, forming the ‘social network.’ (Cheney & Seyfarth 2007, Uddin et al. 2007, Wheatley et al. 2007, Barsalou in press a, Rizzolatti & Craighero 2004)

3. Greater social and cultural complexity paired with the motivation to cooperate and share mental states with others (Tomasello et al. 2005, Herrmann et al. 2007), possibly co evolutionary influences of social complexity, theory of mind (Dunbar 1998, Dunbar & Shultz 2007) as well as technological advances (Reader and Laland 2002, Reader 2003) and brain expansion.

4. higher ability of displaced, goal-directed an planning simulation of physical categories (physical stance, folk physics) functional categories (design stance, folk biology, mechanics) and intentional categories (intentional stance, folk psychology, ToM) aiding survival and reproductive success trough comprehensive prediction in dangerous environments and socially complex groups (Dennett 1987, Poirier et al. 2005, Tooby & DeVore 1987, Ryder & Favorov 2001)

5. Evolution of extensive symbolic capacities and ‘protolanguage’(which I haven’t addressed here) aided among other factors by displaced frontal control and other selective pressures such as the need to communicate displaced information, share intentions and cooperate, foraging, competition, sexual selection such as display of genetic fitness, establishment of trust, etc. etc. (Deacon 1998, Bickerton 2006, Jackendoff 2002, Pinker 1994, Tomasello et al. 2005, Desalles 2007, Franks and Rigby 2002).

6. Further enhancement of symbol-usage through interactions between language and embodied simulation and ‘symbolic theft’ (embodied-experience to language mapping) (Barsalou in press b, Cangelosi et al. 2002)

7. Evolutionary/cultural feedbacks from language to the conceptual system (Lupyan 2006, Burling 2005, Barsalou 2005, in press a) and further influence of metaphorical structure to language (Lakoff and Johnson, 1987, 1999). The ability to blend mental spaces together and form what-if structures and envision technological/cultural innovations, and goal-directed actions (Turner 2003, Miller et al. 2002,Cheney and Seyfarth 2007) Cheney & Seyfarth write that if you search for what-if on Google you’ll get about 150,000,000 hits, which as they say, might be too much of a good thing.

Oh yeah, and mirror neurons also possibly played a rule in language evolution (Arbib 2005). And I didn’t say anything about syntactic/grammatical evolution (Jackendoff 2002) And I forgot recursion (Hauser et al. 2002) as well. And as almost everyone else I’m sure the Baldwin Effect has something important to do with language evolution (Jackendoff 2002, Kirby 2000). Neither did I address the fact that… oh well, as you see, language evolution is a pretty darn complex interdisciplinary field, but I think I pinpointed some of the (if not all) key issues critical for the evolution of language and the human mind. Hope you enjoyed my digressions inspired by Cheney and Seyfarth’s book. Cheers.

References:

Arbib, Michael A. 2005. “From monkey-like action recognition to human language: An evolutionary framework for neurolinguistics.” Behavioral and Brain Sciences 28: 105-167

Barsalou, Lawrence W. 2005. “Continuity of the conceptual system across species.” Trends. Cog. Sc. 9.7: 309-311.

Barsalou, Lawrence W. In press. “Grounded Cognition.” In: Annual Review of Psychology 59

Barsalou, Lawrence W. in press b. “Grounding symbolic operations in the brain’s modal systems.” Embodied grounding: Social, cognitive, affective, and neuroscientific approaches. Eds. G.R. Semin & E.R. Smith. New York: Cambridge University Press.

Bickerton, Derek. 2006. “Language Evolution”

Burling, Robbins. 2005. The Talking Ape. Oxford: OUP

Cangelosi, A., Greco, A., & Harnad, S. 2002. “Symbol Grounding and the Symbolic Theft Hypothesis”. Simulating the Evolution of Language. Eds. A.Cangelosi & D. Parisi . London: Springer

Cheney, Dorothy L. and Robert M. Seyfarth. 2007. Baboon Metaphysics: The Evolution of a Social Mind. Chicago: University of Chicago Press.

Deacon, Terrence William 1998. The Symbolic Species: The Co-evolution of Language and the Brain. New York / London: W.W. Norton.

Dennett, Daniel C. 1987. The Intentional Stance. Cambridge, M.A.: Bradford Books.

Desalles, Jean-Louis. 2007. Why We Talk. Oxford: OUP.

Dunbar, Robin 1998. “Theory of Mind and the Evolution of Language.” In: James
R. Hurford, Michael Studdert-Kennedy and Chris Knight (eds.). Approaches to the Evolution of Language. Social and Cognitive Bases. Cambridge: Cambridge University Press

Dunbar, R. I. M. and Susanne Shultz. 2007.“Evolution in the Social Brain” Science 317: 1344-1347

Franks, Bradley and Kate Rigby 2005. “Deception and mate selection: some implications for relevance and the evolution of language” Language Origins: Perspectives on Evolution. Ed. Maggie Tallerman. Oxford: OUP.

Gil-da-Costa, Ricardo, Allen Braun, Marco Lopes, Marc D. Hauser, Richard E. Carson, Peter Herscovitch and Alex Martin. 2004. “Toward an evolutionary perspective on conceptual representation: Species-specific calls activate visual and affective processing systems in the macaque.” PNAS 101.50: 17516–17521.

Hauser, Marc D., Noam Chomsky and W. Tecumseh Fitch 2002. “The Faculty ofLanguage: What Is It, Who Has It, and How Did It Evolve?” In: Science 298, 1569-1579.

Herrmann, Esther, Josep Call, María Victoria Hernández-Lloreda, Brian Hare, and Michael Tomasello. 2007. “Humans Have Evolved Specialized Skills of Social Cognition: The Cultural Intelligence Hypothesis.” Science 317: 1360-1365.

Jackendoff, Ray. 2002.. Foundations of language: brain, meaning, grammar, evolution. Oxford: Oxford University Press.

Kirby, Simon 1998. “Fitness and the Selective Adaptation of Language.” In: James R. Hurford, Michael Studdert-Kennedy and Chris Knight (eds.). Approaches to the Evolution of Language. Social and Cognitive Bases. Cambridge: Cambridge University Press, 359-383.

Lakoff, George, and Mark Johnson 1980. Metaphors we live by. Chicago: University of Chicago Press.

Lakoff, George and Mark Johnson. 1999. Philosophy in the Flesh: The Embodied Mind and its Challenge to Western Thought. New York: Basic Book

Lupyan, Gary. 2006. “Labels Facilitate Learning of Novel Categories.” The Evolution of Language: Proceedings of the 6th International Conference. Eds. A. Cangelosi, A.D.M. Smith & K.R. Smith Singapore: World Scientific,190-197

Miller, Earl K., David J. Freedman and Jonathan D. Wallis 2002. “The Prefrontal Cortex: Categories, Concepts and Cognition.” In: Phil. Trans. R. Soc. Lond. B 357: 1123–1136

Poirier, Pierre, Benoit Hardy-Vallée and Jean-Frédéric Depasquale.2005. “Embodied Categorization.” Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier, 2005.

Pinker, Steven 1994. The Language Instinct: The New Science of Language and Mind. London: Lane Penguin Press.

Reader, S.M. 2003. “Relative brain size and the distribution of innovation and social learning across the nonhuman primates.” The Biology of Traditions: Models and Evidence. Eds. D.M. Fragaszy and S. Perry, 56-93.

Reader, S.M. and K.N. Laland. 2002. “Social Intelligence, innovation, and enhanced brain size in primates” PNAS 99: 4436-4441.

Rilling, James K. 2006. Human and NonHuman Primate Brains: Are They Allometrically Scaled Versions of the Same Design? Evolutionary Anthropology 15: 67-77.

Ryder, Dan and Oleg V. Favorov. 2001. “The New Associationism: A Neural Explanation for the Predictive Powers of Cerebral Cortex.” Brain and Mind 2.2. 161-194.

Tomasello, Michael, Malinda Carpenter, Josep Call, Tanya Behne, and Henrike Moll. 2004. “Understanding and Sharing Intentions: The Origins of Cultural Cognition.” Behavioral and Brain Sciences 28.4

Tooby, John and Irven DeVore 1987. “The Reconstruction of Hominid Rvolution Through Strategic Modelling.” The Evolution of Human Behavior: Primate Models. Ed. W.G. Kinzey. Albany: SUNY.

Turner, Mark. 2003. “Double-Scope Stories.” Narrative Theory and the Cognitive Sciences. Ed. David Herman

Rizzolatti, Giacomo and Laila Craighero. “The Mirror-Neuron System.” Annual Review of Neuroscience 27 (2004): 169–192.

Uddin, Lucina Q., Marco Iacoboni, Claudia Lange and Julian Paul Keenan. 2007.“The Self and Social Cognition: The Role of Cortical Midline Structures and Mirror Neurons.” Trends in Cognitive Sciences 11.4 53-157.

Wheatley, Thalia, Shawn C. Milleville and Alex Martin. “Understanding Animate Agents: Distinct Roles for the Social Network and Mirror System.” Psychological Science 18.6 (2007): 469-474.

Evolutionary Metaphysics IV

Since I drifted away from discussing baboons and Cheney and Seyfarth’s book quite a bit, I decided to name this post (jokingly) ‘Evolutionary Metaphysics, because, according to the OED, metaphysics includes questions about

"the underlying concepts or first principles on which a particular branch of knowledge is based."

OK, there actually is already such a field, called evolutionary epistemology, or its evil twin brother, evolutionary psychology, but I’ll still go with this title.
In my last post, I considered some proposals how our – in some parts species-continuous – conceptual system had been extended. Deacon (1998) and Barsalou (2005) both observed the higher frontal cortical control which humans show compared to other animals. Whereas Deacon proposed that we had a ‘front heavy’ cognitive style, Barsalou broke our conceptual extensions down into component parts. Some of them explicitly seem to be reliant on frontal control, such as Mental Time Travel and Conceptual Blending.
Another proposal for a human specialization similar to these traits is cause-and-effect reasoning, in order to outwit defences of plants and animals, as well as competitors (Tooby and DeVore 1987). The enhancement of these capacities in humans is congruent with the fact that the prefrontal cortex synthesizes the information received from other areas into representations of concepts, rules and contingencies, and that this structure is especially elaborate in primates and especially so in humans (Miller et al. 2002, Deacon 1998, Ivry & Knight 2002). Prefrontal enlargement could have led to enhanced cognitive control over the conceptual system, and thereby to a greater cognitive control over our own actions and their goals.

However, when taking into account human ToM-abilities, there seems to be a lot more to it than just prefrontal enlargement. How wan we take different perspectives and attribute false beliefs to others? Regarding the blending of incompatible concepts, Mark Turner asks: ”How can we fire up incompatible mental patterns simultaneuously […] Evolutionary, how did our species develop this ability?” (Turner 2003: 118). What are the evolutionary steps complementing higher frontal control?
Cheney and Seyfarth amassed evidence for the existence of mental representations in baboons; neuroimaging studies showed the same for macaque monkeys (Gil-da-Cost et al. 2004). Following Barsalou (2005) in assuming a common architecture for human and animal conceptual systems, what are the foundations of social cognition in other animals, on which human ToM-abilities were built?
One part of the answer seems to lie in the discovery of ‘mirror neurons’ “a particular class of visuomotor neurons, originally discovered in area F5 of the monkey premotor cortex, that discharge both when the monkey does a particular action and when it observes another individual (monkey or human) doing a similar action” (Rizzolatti et al. 2001: 661). A similar mirror neuron system crucial to the understanding of action, imitation, and also involved in language is argued to exist in humans (Rizzolatti/Craighero 2004). Mirror neurons sometimes seem to be hyped as the answer to every open question in the cognitive studies, but at the moment no one really seems to know what to conclude from them.

So how do we understand others? Gallese and his colleagues (2004) propose that we understand others and infer mental states to them by simulating their actions in our ‘mirror system.’ These proposals are in accordance with Barsalou’s view of conceptualization as integrated simulations of experience-based concepts in our conceptual system (Barsalou in press) But as Barsalou himself stresses, mirror circuits seem to be part of a larger system which also involves inhibitory processes that keep simulated and own mental states apart from each other (Decety and Grazes 2006) and the establishment of joint attention (Sebanz et al. 2006).
This larger system is sometimes identified as a functional system called ‘social network’ which integrates contributed information from others systems into the mental representation of an animate being (Wheatley et al. 2007). Wheatley and colleagues found that the mirror system does not respond selectively to biological actions, but to actions in general. The failure of the mirror system to be modulated by the interpretation of animacy when observing or simulating an action makes it unlikely to be the origin of general social cognition. Instead, Wheatley and his colleagues argue that inferring animacy is done by the ‘social network’ and propose to see the mirror system as a general simulation machinery which is employed in tandem by the social network, imagery and other cognitive processes.They conclude that the social network’s ability to infer animacy should be seen as an important component of, as well as an evolutionary precursor to our complex social cognition and Theory of Mind-abilities.

Yet another component of the social network may be the so-called cortical midline structures (CMS), which process information about others and the self in more evaluative and abstract and ways (Uddin et al. 2007). Uddin and her colleagues see CMS and the mirror system as interactive components. They propose that the mirror system is responsible for the ability to map representations of others onto our own mental architecture, and that the CMS evaluates and underscores these mappings. It would be interesting to know if CMS exist in non-human primates and other animals, and if not, if there are possible homologues. Another question is if Wheatley et al.’s and Uddin et al’s proposals are compatible. I, for instance, have no idea. In my next post I will sum up my previous observations and see if I can draw some rough skeletal evolutionary scenario from it.

References:

Barsalou, Lawrence W. In press. “Grounded Cognition.” In: Annual Review of Psychology 59

Barsalou, Lawrence W. 2005a. “Continuity of the conceptual system across species.” Trends. Cog. Sc. 9.7: 309-311.

Deacon, Terrence William 1998. The Symbolic Species: The Co-evolution ofLanguage and the Brain. New York / London: W.W. Norton.

Decety, Jean, & Julie Grèzes. 2006. “The power of simulation: Imagining one's own and other's behavior.” Brain Research 1079: 4-14.

Gil-da-Costa, Ricardo, Allen Braun, Marco Lopes, Marc D. Hauser, Richard E. Carson, Peter Herscovitch and Alex Martin. 2004. “Toward an evolutionary perspective on conceptual representation: Species-specific calls activate visual and affective processing systems in the macaque.” PNAS 101.50: 17516–17521.

Ivry Richard and Robert T. Knight. 2002. “Making order from chaos: the misguided frontal lobe” Nature Neuroscience 5.5: 394-396.

Miller, Earl K., David J. Freedman and Jonathan D. Wallis 2002. “The Prefrontal Cortex: Categories, Concepts and Cognition.” In: Phil. Trans. R. Soc. Lond. B 357: 1123–1136

Rizzolatti, Giacomo and Laila Craighero. “The Mirror-Neuron System.” Annual Review of Neuroscience 27 (2004): 169–192.

Rizzolatti, Giacomo, Leonardo Fogassi and Vittorio Gallese. “Neurophysiological Mechanisms Underlying the Understanding and Imitation of Action.” Nature Reviews Neuroscience 2 (2001): 661–670.

Sebanz, N., Bekkering, H., & Knoblich, G. 2006. Joint action: Bodies and minds moving together. Tr. Cog. Sc. 10: 70-76.

Tooby, John and Irven DeVore 1987. “The Reconstruction of Hominid Rvolution Through Strategic Modelling.” The Evolution of Human Behavior: Primate Models. Ed. W.G. Kinzey. Albany: SUNY.

Uddin, Lucina Q., Marco Iacoboni, Claudia Lange and Julian Paul Keenan. 2007. “The Self and Social Cognition: The Role of Cortical Midline Structures and Mirror Neurons.” Trends in Cognitive Sciences 11.4 (2007): 153-157.

Wheatley, Thalia, Shawn C. Milleville and Alex Martin. “Understanding Animate
Agents: Distinct Roles for the Social Network and Mirror System.” Psychological Science 18.6 (2007): 469-474.

Baboon Metaphysics III: Links with other Fields of Cognitive Science

In my last post I argued that “Baboon Metaphysics” only mentioned half of the story of what makes the human conceptual system unique. What Cheney and Seyfarth did not address in their still absolutely excellent and insightful book, is the way our conceptual system has been extended in respect to that of other animals, and the way language may interact with conceptualization and other cognitive processes, instead of simply being the expression of cognitive processes absolutely independent from it. (Although I don’t want to attribute such a view to Cheney and Seyfarth just because they haven’t said anything about it, this theory still seems to be quite prominent. See, for example, Edmund Blair Bolles' review of Steven Pinker’s new book “The Stuff of thought (2007) ).
In the words of Robbins Burlings (2005): “What has language done to us?” Work by Gary Lupyan and others shows that there is evidence that language, thinking, and concepts interact and that language helps us organize and categorize the world and sometimes alters how we process information (Kenneally 2007: 106-111). This is certainly not a return to strong versions of the Sapir-Whorf thesis, considering that Cheney and Seyfarth clearly showed that there are concepts and conceptualization without language, and evidence that language itself is partly grounded in embodied cognition (Lakoff and Johnson 1980, Lakoff and Johnson 1999). But these interactive processes, and the way our own extended conceptual abilities rely on enhanced cognitive supplements to our basic neural architecture, are definitely part of the whole picture.

In my last post, I mentioned that Barsalou (2005) argued that frontal lobe control is a critical factor enhancing the displacement- and computation-abilities of conceptual simulation, and therefore a crucial factor of defining what makes the human extended conceptual system different from animal mental representations, which evolutionary are the basic architecture for our cognitive abilities, and which Cheney and Seyfarth described marvelously. Terrence Deacon has a similar proposal what makes us human. According to him

“The prominent enlargement of the prefrontal cortex and the correlated shifts in connection patterns that occurred during human brain evolution introduced strong biases into the learning process and gave human prefrontal circuits a greater role in many neural processes unrelated to language. Though intense selection was directed toward this one aspect of mind and brain, its secondary effects have also ramified to influence the whole of human cognition. (Deacon 1998: 417)

Because the prefrontal cortex is the most important structure that supports symbolic reference (Deacon 1998: 266) and in human beings, prefrontal circuits play a greater role in all neural processes of the brain than in any other species (Deacon 1998: 265), we are “The Symbolic Species” inhabiting mental worlds mediated by thousands of hierarchical structured symbol-symbol relationships (see also Kenneally’s (2007) prelude for a quite poetic description of the semiotic universes we create and communicate about) intertwined with our physical lives, our embodied experience of the outside world. As I mentioned in my last post Barsalou (2005), too, sees our symbolic capacities mediated by greater frontal control as crucial:

“What results is control of the distributed property architecture to represent components of situations and to combine them in novel ways.“

These combination of representations into an ‘integrated simulation’, can be found in another field of inquiry, namely mental images:

“Mental images need not result simply from the recall of previously perceived objects or events; they can also be created by combining and modifying stored perceptual information in novel ways.” (Kosslyn et al. 2001).

Interestingly “most of the neural processes that underlie like-modality perception are also used in imagery; and imagery, in many ways, can ‘stand in’ for (re-present, if you will) a perceptual stimulus or situation“ (Kosslyn et al. 2001). This supports Barsalou’s view that conceptualization consists of integrated “reenactments of perceptual, motor, and introspective states acquired during experience with the world, body, and mind “ (Barsalou in press). Also interesting in this regard is Mark Turner’s stance at what makes us uniquely human: conceptual blending - the integration of two mental spaces/conceptual structures to form a new one, enabling mental time travel and escape, as well as what-if relations. Turners describes it as “a basic human mental operation, with constitutive and governing principles. It played a crucial role, probable the crucial role, in the descent of our species over the last fifty or one hundred thousand years” (Turner 2003).

By the way, Edmund Blair Bolles has posted a great discussion of a paper by Don Ross which deals with the evolution of human culture and joint attention. Go check it out!

References:
Barsalou, Lawrence W. 2005a. “Continuity of the conceptual system across species.”
Trends. Cog. Sc. 9.7: 309-311.

Barsalou, Lawrence W. In press. “Grounded Cognition.” In: Annual Review of Psychology 59

Burling, Robbins. 2005. The Talking Ape. Oxford: OUP.

Cheney, Dorothy L. and Robert M. Seyfarth. 2007. Baboon Metaphysics: The Evolution of a Social Mind. University of Chicago Press, Chicago

Deacon, Terrence William 1998. The Symbolic Species. The Co-evolution of
Language and the Brain. New York / London: W.W. Norton.

Pinker, Steven 2007. The Stuff of Thought: Language as a Window into Human Nature. New York: Viking.

Kenneally, Christine. 2007. The First Word: The Search for the Origins of Language. New York: Viking.

Kosslyn, Stephen M., Giorgio Ganis and William L. Thompson. 2001.“Neural Foundations of Imagery.” Nature Reviews Neuroscience 2: 635-642.

Lakoff, George, and Mark Johnson 1980. Metaphors we live by. Chicago: University of Chicago Press.

Lakoff, George and Mark Johnson. 1999. Philosophy in the Flesh: The Embodied Mind and its Challenge to Western Thought. New York: Basic Book

Turner, Mark. 2003. “Double-Scope Stories.” Narrative Theory and the Cognitive Sciences. Ed. David Herman

Baboon Metaphysics II

In my last post, I wrote about Dorothy Cheney’s and Robert Seyfarth’s new book “Baboon Metaphysics” and their claim that

“Baboons teach us that it is possible to have a complex society based on cognitive processes that are both computational and representational without either language or a theory of mind. Concepts (of a sort) can exist without words; computation can occur without grammar, Along with many other species of animals, baboons provide us with a natural experiment that allows us to ask “What it thought – what can it possibly be – without language and a theory of mind.?” (p. 276)

In their book, the authors refer to a wealth of other literature about animal communication, cognition and human evolution, and I will write about some of these papers from then to then.

One important implication of Cheney and Seyfarth’s argument is the “Continuity of the conceptual system across species“ (Barsalou 2005a), which outright contradicts the strong versions of the Sapir-Whorf-thesis, radical constructivism and cultural relativism. The Conceptual system is a “system distributed throughout the brain that represents knowledge about the world“(Barsalou 2005b: 621). Primates and monkeys have rich conceptual systems, they therefore can think without language. Conceptual representation in humans and monkeys has common neural substrates, suggesting how human cognition build upon these evolutionary precursors (Gil-da-Costa 2004).
Additional systems seem to have extended the conceptual abilities of humans significantly (Barsalou 2005a). And this is where, Cheney and Seyfarth’s “First thought, then language” ceases to tell the whole story. I don’t think this can really be called a shortcoming of the book, but I’m a bit disappointed that the authors didn’t at least hint at what makes our conceptual system different from that of other animals, and in which ways it could be influence by language. Though they stress that the human ability to have a theory of mind “favored an ability to speak, expand one’s vocabulary, and combine words in sentences to convey novel meanings” (p.281) and they concur with Tomasello et al. (2005) that “shared intentionality”, the motivation to cooperate with others and to share intentions and mental states with them, is a crucial principle of humanness, culture, and language, they still don’t go further than “Thought came first; speech and language appeared later, as its expression”(p.281).
But for me, the story doesn’t end here. Cheney and Seyfarth stress the fact that the “same basic architecture for representing knowledge is present in humans” (Barsalou 2005a), and rightly so. As Barsalou (2005b) puts it, conceptualization processes work

"via integrated simulations of agents, objects, settings, actions, and introspections. On recognizing a familiar type of category instance, an entrenched situated conceptualization associated with it becomes active to provide relevant inferences via pattern completion". (Barsalou 2005b: 645)

This pattern completion seems to be an essential feature of all cognitive systems, because it allows an organism to prepare for and predict actions and events, thus aiding survival. (Barsalou 2005). Many neuroscientists are convinced that the brain’s main task is prediction in order to survive in dangerous environments (Ryder/Favorov 2001), and, we can add with Cheney and Seyfarth, to be able to function in large social groups. With a theory of mind, humans have much better predictive strategies at hand, and thus are even better equipped to cooperate and function in large societies. This is one of the key themes in “Baboon Metaphysics.” But what else makes our conceptual system different, and how so? Besides having a ToM, Barsalou (2005a) argues that another uniquely human complement of the conceptual system is that they “represent situations that are completely unrelated to the current situation,” enhancing learning and future performance by mentally simulating past events, an maximizing the achievement of goals by simulation of planned events in the future.

Barsalou stresses the importance of the frontal lobe for such activations. He adds language as another possibility for the extensions of the human conceptual system. Barsalou speculates that “the linguistic system provides exquisite control over the simulation system as it represents non-present situations.” Thus, what could make humans essentially different, along with higher social ToM-competence, may be their “control of the distributed property architecture to represent components of situations and to combine them in novel ways.“ This ability again is hugely reliant on frontal activation. These observations resonate with Terrence Deacon’s (1998) depiction of our ‘front-heavy” cognitive style, which makes us “The Symbolic Species”, Mark Turner’s theory of Conceptual Blending, as well as with work by Stephen Kosslyn, which I will address in my next post on the book.
In sum, this combinations of Cheney and Seyfarth’s work with Barsalou’s and others considerations about the human conceptual system is, I think, extremely interesting, and makes “Baboon Metaphysics” – coming from one side and looking to meet with research such as Barsalou’s, Deacon’s, and Turner’s – an important milestone in our quest of unravelling the human mind.

References:
Barsalou, Lawrence W. 2005a. “Continuity of the conceptual system across species.” Trends. Cog. Sc. 9.7: 309-311.

Barsalou, Lawrence W. 2005b “Situated Conceptualization.” Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier. 619-650.

Cheney, Dorothy L. and Robert M. Seyfarth. 2007. Baboon Metaphysics: The Evolution of a Social Mind. Chicago: University of Chicago Press.

Deacon, Terrence William. 1998. The Symbolic Species: The Co-evolution of Language and the Brain. New York / London: W.W. Norton.

Gil-da-Costa, Ricardo, Allen Braun, Marco Lopes, Marc D. Hauser, Richard E. Carson, Peter Herscovitch and Alex Martin. 2004. “Toward an evolutionary perspective on conceptual representation: Species-specific calls activate visual and affective processing systems in the macaque.” PNAS 101.50: 17516–17521.

Ryder, Dan and Oleg V. Favorov. 2001. "The New Associationism: A Neural Explanation for the Predictive Powers of Cerebral Cortex.” Brain and Mind 2.2. : 161-194.

Tomasello, Michael, Malinda Carpenter, Josep Call, Tanya Behne, and Henrike Moll. 2004. “Understanding and Sharing Intentions: The Origins of Cultural Cognition.” Behavioral and Brain Sciences 28.5

27th Four Stone Hearth Carnival

The latest installment of the Four Stone Hearth Anthropologycarnival is up over at Sorting Out Science, hosted by Sam Wise. 
This time's carnival features tons of interesting material (including a link to one of my posts - woohoo!) and you really should go check it out. 

By the way, I just saw last week's episode of House and quite dissapointed that it seems as if Giovannini's Mirror Syndrome doesn't really exist - Unconsciously mirroring other people due to a malfunction of the human "mirror system" would be quite an interesting diagnosis. (OK... I'm a nerd.)

P.S. there actually seems to be something similar to the case found in the House Episode, but it seems as it doesn't have anything to do with the mirror system. (So I don't have any academic excuse to look it up, except that it's sounds interesting)

Baboon Metaphysics I

In their new Book, „Baboon Metaphysics“, Dorothy Cheney and Robert Seyfarth have some interesting things to say about language evolution. The book's title refers to a statement Charles Darwin scribbled in one of his notebooks:

"Origin of man now proved. – Metaphysics must flourish. – He who understands baboon would do more towards metaphysics than Locke.”

As Dan Dennett (1995) puts it, the idea of evolution is universal acid, transforming every world-view, yielding new perspectives on every aspect of life, impacting on our view of what it is to be human, and what makes us human.
Through their research on baboons in the Okavango Delta in Botswana, Cheney and Seyfarth have gained new insights into how

"evolution acts on the communication and cognition of animals that live in large social groups.” (p. 251)

Baboons show remarkable skills in keeping track not only of the relationships between themselves and other group members, but also in recognizing the “close bonds that exist among other members of their groups.” To test this, Cheney, Seyfarth and their team did some ingenious experiments by playing simulated vocal communications of existing group members that violated the linear transitive dominance hierarchy of the group, for example, fear barks of higher female which were directed at a female of a lower rank. The baboons looked towards the speaker for a longer period of time if the recording violated the actual hierarchy, suggesting that baboons have a mental representation and therefore expectations of the interactions and hierarchy systems within their group. Other experiments also showed that baboons are indeed quite sophisticated when it comes to understanding the complexities of their social group.
Two implications for language evolution, are I think, especially interesting. First, one crucial component of our ability to use language is having a Theory of Mind, that is the ability to attribute mental states to others. And

“although baboons and other monkeys probably do not recognize when someone is attempting to manipulate their beliefs, they may recognize when someone is attempting to manipulate their intent. They integrate social cues, gaze direction, and call type when making these assessments and when announcing their intentions to others. A rudimentary understanding of intentions and motives represents a crucial first step toward a communication system like language, in which speakers and listeners routinely assess each other’s motives, beliefs, and knowledge.” (p. 183)

Baboons certainly do not have a full-fledged Theory of Mind like humans, and in some aspects fail rather poorly at recognizing other’s mental states, for example the anxiety and fear their children endure during water-crossing, where they seem to assume that, when they can make the water crossing, everyone can, or when trying to hide from an aggressive male. But they hint at how a social mind evolves, and what the cognitive precursors for our own ToMs probably looked like.
The other implication regards the baboons' ability to form mental representations, concepts of the outside world. This suggests an evolutionary scenario in which thought came first, then language. as Cheney and Seyfarth put it: “3. In primate groups, natural selection has favored individuals who can form mental representations of other individuals, their relationships, and their motives” (p. 251). But they even go further:

“4. This social knowledge constitutes a discrete, combinatorial system of representations - a language of thought – that shares several features with human language. 5. The language of thought that has evolved in baboons and other primates is a general primate characteristic whose appearance predates the evolution of spoken language in our hominid ancestors. 6. The prior evolution of social cognition created individuals who were preadapted to develop language. 7. Several features thought to be unique to language – for example, discrete combinatorics and the encoding of propositional information – were not introduced by language. They arose, instead, because understanding social life and predicting others’ behavior requires a particular style of thinking.” (p. 251f.)

The last part is especially interesting. The idea of the ‘language-ready brain’ is of course not new, and is embraced by many scholars interested in the evolution of language, but the claim that a “social syntax” with a recursive structure is the evolutionary foundation of modern language, is, I think, quite compelling, although it contradicts Derek Bickerton’s (1990) notion of a “protolanguage” without syntax. This, too, refutes Alison Wray’s (2002) hypothesis that technology and culture stagnated between 1,4 and 0,5 million years because there were no names for actions or things, since primates clearly can conceptualize actions, and therefore a proto-language should be able to express them.
(A better explanation for this stagnation is given by Ray Kurzweil in his TED-Talk, namely the inherent exponential nature of technological progress, which allows for ever faster periods of rapid acceleration.)
It is however, in accordance with the claim made by Hauser, Chomsky and Fitch in 2002 that recursion and its mappings to the interfaces as they form the uniquely human part of the human language faculty “may have evolved for reasons other than language” (Hauser/Chomsky/Fitch 2002: 1571) and that recursion could be an exaptation that originally “evolved to solve other computational problems such as navigation, number quantification, or social relationships” (Hauser/Chomsky/Fitch 2002: 1578), although Hauser, Chomsky, Fitch insisted that recursion in general was uniquely human.
In my next post, I will come back to what it means for our conceptual system to be build upon evolutionary older foundations.

References:
Bickerton, Derek. 1990. Language and Species. University of Chicago Press, Chicago.

Dennet, Daniel C. 1995. Darwin’s Dangerous Idea: Evolution and the Meanings of Life. New York: Simon & Schuster.

Cheney, Dorothy L. and Robert M. Seyfarth. 2007. Baboon Metaphysics: The Evolution of a Social Mind. University of Chicago Press, Chicago.

Hauser, Marc D., Noam Chomsky and W. Tecumseh Fitch 2002. “The Faculty of Language: What Is It, Who Has It, and How Did It Evolve?” In: Science 298, 1569-1579.

Wray, Alison.“Dual Processing in Protolanguage: Performance without Competence.” In: Wray, Alison. (Ed.) The Transition to Language. Studies on the Evolution of Langauge 2. Oxford, OUP.

LolAntz

In my last posts I wrote about the question how AI and Robotics can tell us something about the architecture of (simple) biological systems. In this post I’ll give an example of how the study of simple organisms, augmented by AI and robotics, can give us information about the structure of cognitive systems.
Studying ant’s navigational skills is such an example. It can tell us something about the evolution of cognitive mechanisms in general because an ant's “domain-specific processing modules” (Wehner 2003a: 585) show signs of modular adaptation, that is, it seems to have

“evolved to solve particular problems encountered by Cataglyphis during its foraging lifetime.” (Wehner 2003a: 579).

In detail, the ant’s navigational toolkit consists of:

“its skylight (polarization) compass, its path integrator, its view-dependent ways of recognizing places and following landmark routes, and its strategies of flexibly interlinking these modes of navigation to generate amazingly rich behavioural outputs.“ (Wehner 2003a: 579)

The sophistication of these synchronically orchestrated navigational modules is quite amazing given that they are found in a brain that weighs 0.1 mg. The human brain weighs about 13 million times at much, about 1,300 g (Jones 2004).
It is probable that our brains too, consist of cognitive mechanisms (and learning mechanisms) which are

"hierarchically nested adaptive specializations, each mechanism constituting a particular solution to a particular problem” (Gallistel 2000).

Another fascinating feature of the ant’s navigational toolkit is its context-dependency . Cataglyphis doesn’t create a ‘mental map’ of its environment, but has a highly egocentric perspective and employs a ‘path integrator’, a permanently updated system informing the ant “about its current position relative to its point of departure”, a little like Ariadne’s thread. (Wehner 2003a).
If the ant is picked up and placed somewhere else, it as a hard time getting home (if it even makes it at all) because the neurological ‘thread’ of the ant’s navigational system isn’t connected to the starting point anymore. When the path-integration vector (the ‘thread’) is displaced, what otherwise would leave the ant straight home is now worthless, because any information about the environment is strictly evaluated in relationship to the ant itself. Therefore the navigational toolkit of Cataglyphis is not only an example of domain-specific adaptation, but also of embodied intelligence (Wehner 2003b).

Interestingly, an experiment by Floreano and Nolfi (1996) in which robots had to explore an area (which I described in my first post) led to the development of very similar mapping-strategies in the robot’s self-organizing neurons. (Wehner and his colleagues also suceeded in building a mobile robot modeling the navigational skills of Cataglypghis, with comparable results.)
This means that both in Cataglyphis and simple artificial systems,

“There is no categorization of the environment that is independent of it” (Poirier et al. 2005: 751)

These “lessons from Cataglyphis” (Wehner 2003b), crucial as they are for understanding human cognition, surely aren't the whole story, especially as there is evidence for a dual-system account of human cognition, consisting of a ‘primitive’, fast , automatic and strongly modular system, and a more-fluid, conscious, cross-domain system. (Evans in press) Additionally,

“One should never underestimate the functional economy of nervous systems: once they have been adapted, over evolutionary time, to the principal physical properties of a predictable environment, they can employ comparatively simple neural strategies to solve quite sophisticated computational tasks.” (Wehner 2003a: 582)

A higher-cognitive task like reading, for example, can probably be explained best by the functional economy and plasticity of human brains. For reading, the “capacity to accommodate a broad range of new functions through learning” (Dehaene 2004) and the ability to employ (or ‘recycle’ as Dehaene calls it) neuronal circuits which serve a similar or related function seems to be essential.
Of course there is still a long way from systems showing properties of embodiment to systems that have internal perspective, but the research discussed in this as well as other posts makes it pretty clear that embodiment is without doubt a crucial component not only of all sensori-motor systems, but also of cognitive systems (Cruse 2003),

P.S.: please note that the ant in the picture isn't a desert ant but a leafcutter ant. I just couldn't find a useful picture of cataglyphis to toy around with ;-)

References:

Cruse, Holk. 2003: “The Evolution of Cognition – A Hypothesis.” Cognitive Science 27: 135–155

Dehaene, Stanislas. 2004. “Evolution of human cortical circuits for reading and arithmetic: The “neuronal recycling” hypothesis." From monkey brain to human brain. Eds. S. Dehaene, J. R. Duhamel, M. Hauser & G. Rizzolatti Cambridge, MA: MIT Press.

Evans, Jonathan St. B.T. in press. “Dual-Processing Accounts of Reasoning, Judgment, and Social Cognition.” Annual Review of Psychology 59

Floreano, Dario, and Francesco Mondada (1996), “Evolution of homing navigation in a real mobile robot”, IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics 26:396–407.

Gallistel, C.R. 2000. „The Replacement of General-Purpose Learning Models with Adaptively Specialized Learning Modules.” The Cognitive Neurosciences. 2d ed. Ed. M.S. Gazzaniga. Cambridge, MA: MIT Press: 1179-1191.

Jones, Owen D. 2004. “Law, Evolution, and the Brain: Applications and Open Questions.” Proclamations of The Royal Society of London B: Biological Sciences 359: 1697-1707.

Poirier, Pierre, Benoit Hardy-Vallée and Jean-Frédéric Depasquale.2005. “Embodied Categorization.” Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier, 2005.

Wehner, Rüdiger. 2003a. “Desert ant navigation: how miniature brains solve complex tasks.” Journal of Comparative Physiology A: Neuroethology, Sensory, Neural, and Behavioral Physiology 189: 579–588

Wehner, Rüdiger. 2003b. “Blick ins Cockpit von Cataglyphis” Naturwissenschaftliche Rundschau 56.3: 134-140.